Modelling the effects of land use and climate changes on hydrology in the Ursern Valley, Switzerland

While many studies have been conducted in mountainous catchments to examine the impact of climate change on hydrology, the interactions between climate changes and land use components have largely unknown impacts on hydrology in alpine regions. They need to be given special attention in order to devise possible strategies concerning general development in these regions. Thus, the main aim was to examine the impact of land use (i.e. bushland expansion) and climate changes (i.e. increase of temperature) on hydrology by model simulations. For this purpose, the physically based WaSiM-ETH model was applied to the catchment of Ursern Valley in the central Alps (191 km2) over the period of 1983−2005. Modelling results showed that the reduction of the mean monthly discharge during the summer period is due primarily to the retreat of snow discharge in time and secondarily to the reduction in the glacier surface area together with its retreat in time, rather than the increase in the evapotranspiration due to the expansion of the “green alder” on the expense of grassland. The significant decrease in summer discharge during July, August and September shows a change in the regime from b-glacio-nival to nivo-glacial. These changes are confirmed by the modeling results that attest to a temporal shift in snowmelt and glacier discharge towards earlier in the year: March, April and May for snowmelt and May and June for glacier discharge. It is expected that the yearly total discharge due to the land use changes will be reduced by 0.6% in the near future, whereas, it will be reduced by about 5% if climate change is also taken into account. Copyright © 2013 John Wiley & Sons, Ltd.

Impact of normal and shear stresses due to wheel slip on hydrological properties of an agricultural clay loam: Experimental and new computerized approach

The main purpose of this study was to evaluate the effect that mechanical stresses acting under the slipping driving wheels of agricultural equipment have on the soil’s pore system and water flow process (surface runoff generation during extreme event). The field experiment simulated low slip (1%) and high slip (27%) on a clay loam. The stress on the soil surface and changes in the amounts of water flowing from macropores were simulated using the Tires/tracks And Soil Compaction (TASC) tool and the MACRO model, respectively. Taking a 65 kW tractor on a clay loam as a reference, results showed that an increase in slip of the rear wheels from 1% to 27% caused normal stress to increase from 90.6 kPa to 104.4 kPa at the topsoil level, and the maximum shear contact stress to rise drastically from 6.0 kPa to 61.6 kPa. At 27% slip, topsoil was sheared and displaced over a distance of 0.35 m. Excessive normal and shear stress values with high slip caused severe reductions of the soil’s macroporosity, saturated hydraulic conductivity, and water quantities flowing from topsoil macropores. Assuming that, under conditions of intense rainfall on sloping land, a loss in vertical water flow would mean an increase in surface runoff, we calculated that a rainfall intensity of 100 mm h-1 and a rainfall duration of 1 h would increase the runoff coefficient to 0.79 at low slip and to 1.00 at high slip, indicating that 100% of rainwater would be transformed into surface runoff at high slip. We expect that these effects have a significant impact on soil erosion and floods in steeper terrain (slope > 15°) and across larger surface areas (> 16 m2) than those included in our study.

Long-term hydrological dynamics and fire history over the last 2000 years in CE Europe reconstructed from a high-resolution peat archive

Sphagnum peatlands in the oceanic-continental transition zone of Poland are currently influenced by climatic and anthropogenic factors that lead to peat desiccation and susceptibility to fire. Little is known about the response of Sphagnum peatland testate amoebae (TA) to the combined effects of drought and fire. To understand the relationships between hydrology and fire dynamics, we used high-resolution multi-proxy palaeoecological data to reconstruct 2000 years of mire history in northern Poland. We employed a new approach for Polish peatlands – joint TA-based water table depth and charcoal-inferred fire activity reconstructions. In addition, the response of most abundant TA hydrological indicators to charcoal-inferred fire activity was assessed. The results show four hydrological stages of peatland development: moderately wet (from ∼35 BC to 800 AD), wet (from ∼800 to 1390 AD), dry (from ∼1390 to 1700 AD) and with an instable water table (from ∼1700 to 2012 AD). Fire activity has increased in the last millennium after constant human presence in the mire surroundings. Higher fire activity caused a rise in the water table, but later an abrupt drought appeared at the onset of the Little Ice Age. This dry phase is characterized by high ash contents and high charcoal-inferred fire activity. Fires preceded hydrological change and the response of TA to fire was indirect. Peatland drying and hydrological instability was connected with TA community changes from wet (dominance of Archerella flavum, Hyalosphenia papilio, Amphitrema wrightianum) to dry (dominance of Cryptodifflugia oviformis, Euglypha rotunda); however, no clear fire indicator species was found. Anthropogenic activities can increase peat fires and cause substantial hydrology changes. Our data suggest that increased human fire activity was one of the main factors that influenced peatland hydrology, though the mire response through hydrological changes towards drier conditions was delayed in relation to the surrounding vegetation changes.

Atmospheric, oceanic and hydrological polar motion excitation mechanisms based on a combination of geometric and gravimetric space observations

The goal of our study is to determine accurate time series of geophysical Earth rotation excitations to learn more about global dynamic processes in the Earth system. For this purpose, we developed an adjustment model which allows to combine precise observations from space geodetic observation systems, such as Satellite Laser Ranging (SLR), Global Navigation Satellite Systems (GNSS), Very Long Baseline Interferometry (VLBI), Doppler Orbit determination and Radiopositioning Integrated on Satellite (DORIS), satellite altimetry and satellite gravimetry in order to separate geophysical excitation mechanisms of Earth rotation. Three polar motion time series are applied to derive the polar motion excitation functions (integral effect). Furthermore we use five time variable gravity field solutions from Gravity Recovery and Climate Experiment (GRACE) to determine not only the integral mass effect but also the oceanic and hydrological mass effects by applying suitable filter techniques and a land-ocean mask. For comparison the integral mass effect is also derived from degree 2 potential coefficients that are estimated from SLR observations. The oceanic mass effect is also determined from sea level anomalies observed by satellite altimetry by reducing the steric sea level anomalies derived from temperature and salinity fields of the oceans. Due to the combination of all geodetic estimated excitations the weaknesses of the individual processing strategies can be reduced and the technique-specific strengths can be accounted for. The formal errors of the adjusted geodetic solutions are smaller than the RMS differences of the geophysical model solutions. The improved excitation time series can be used to improve the geophysical modeling.

Managing drought economic effects through insurance schemes based on local water availability.

In many arid or semi-arid Mediterranean regions, agriculture is dependent on irrigation. When hydrological drought phenomena occur, farmers suffer from water shortages, incurring important economic losses. Yet, there is not agricultural insurance available for lack of irrigation water. This work attempts to evaluate hydrological drought risk and its economic impact on crop production in order to provide the basis for the design of drought insurance for irrigated arable crops. With this objective a model that relates water availability with expected yields is developed. Crop water requirements are calculated from evapotranspiration, effective rainfall and soil water balance. FAO?s methodology and AquaCrop software have been used to establish the relationship between water allocations and crop yields. The analysis is applied to the irrigation zone ?Riegos de Bardenas?, which is located in the Ebro river basin, northeast Spain, to the main arable crops in the area. Results show the fair premiums of different hydrological drought insurance products. Whole-farm insurance or irrigation district insurance should be preferable to crop specific insurance due to the drought management strategies used by farmers.

Development of a conceptual model of the soil-moisture-plant sub-system of the hydrological cycle

The soil-plant-moisture subsystem is an important component of the hydrological cycle. Over the last 20 or so years a number of computer models of varying complexity have represented this subsystem with differing degrees of success. The aim of this present work has been to improve and extend an existing model. The new model is less site specific thus allowing for the simulation of a wide range of soil types and profiles. Several processes, not included in the original model, are simulated by the inclusion of new algorithms, including: macropore flow; hysteresis and plant growth. Changes have also been made to the infiltration, water uptake and water flow algorithms. Using field data from various sources, regression equations have been derived which relate parameters in the suction-conductivity-moisture content relationships to easily measured soil properties such as particle-size distribution data. Independent tests have been performed on laboratory data produced by Hedges (1989). The parameters found by regression for the suction relationships were then used in equations describing the infiltration and macropore processes. An extensive literature review produced a new model for calculating plant growth from actual transpiration, which was itself partly determined by the root densities and leaf area indices derived by the plant growth model. The new infiltration model uses intensity/duration curves to disaggregate daily rainfall inputs into hourly amounts. The final model has been calibrated and tested against field data, and its performance compared to that of the original model. Simulations have also been carried out to investigate the effects of various parameters on infiltration, macropore flow, actual transpiration and plant growth. Qualitatively comparisons have been made between these results and data given in the literature.

The use of Meteosat satellite data for spatial rainfall estimations and hydrological simulations

Satellite information, in combination with conventional point source measurements, can be a valuable source of information. This thesis is devoted to the spatial estimation of areal rainfall over a region using both the measurements from a dense and sparse network of rain-gauges and images from the meteorological satellites. A primary concern is to study the effects of such satellite assisted rainfall estimates on the performance of rainfall-runoff models. Low-cost image processing systems and peripherals are used to process and manipulate the data. Both secondary as well as primary satellite images were used for analysis. The secondary data was obtained from the in-house satellite receiver and the primary data was obtained from an outside source. Ground truth data was obtained from the local Water Authority. A number of algorithms are presented that combine the satellite and conventional data sources to produce areal rainfall estimates and the results are compared with some of the more traditional methodologies. The results indicate that the satellite cloud information is valuable in the assessment of the spatial distribution of areal rainfall, for both half-hourly as well as daily estimates of rainfall. It is also demonstrated how the performance of the simple multiple regression rainfall-runoff model is improved when satellite cloud information is used as a separate input in addition to rainfall estimates from conventional means. The use of low-cost equipment, from image processing systems to satellite imagery, makes it possible for developing countries to introduce such systems in areas where the benefits are greatest.

Quantifying the effects of temperature and concentration on variable-density flow in numerical modeling of groundwater systems: Implications for predictive uncertainty and data collection

Groundwater systems of different densities are often mathematically modeled to understand and predict environmental behavior such as seawater intrusion or submarine groundwater discharge. Additional data collection may be justified if it will cost-effectively aid in reducing the uncertainty of a model's prediction. The collection of salinity, as well as, temperature data could aid in reducing predictive uncertainty in a variable-density model. However, before numerical models can be created, rigorous testing of the modeling code needs to be completed. This research documents the benchmark testing of a new modeling code, SEAWAT Version 4. The benchmark problems include various combinations of density-dependent flow resulting from variations in concentration and temperature. The verified code, SEAWAT, was then applied to two different hydrological analyses to explore the capacity of a variable-density model to guide data collection. ^ The first analysis tested a linear method to guide data collection by quantifying the contribution of different data types and locations toward reducing predictive uncertainty in a nonlinear variable-density flow and transport model. The relative contributions of temperature and concentration measurements, at different locations within a simulated carbonate platform, for predicting movement of the saltwater interface were assessed. Results from the method showed that concentration data had greater worth than temperature data in reducing predictive uncertainty in this case. Results also indicated that a linear method could be used to quantify data worth in a nonlinear model. ^ The second hydrological analysis utilized a model to identify the transient response of the salinity, temperature, age, and amount of submarine groundwater discharge to changes in tidal ocean stage, seasonal temperature variations, and different types of geology. The model was compared to multiple kinds of data to (1) calibrate and verify the model, and (2) explore the potential for the model to be used to guide the collection of data using techniques such as electromagnetic resistivity, thermal imagery, and seepage meters. Results indicated that the model can be used to give insight to submarine groundwater discharge and be used to guide data collection. ^

Possible climate change impacts on the hydrological and vegetative character of Everglades National Park, Florida

The increasing threat of global climate change is predicted to have immense influences on ecosystems worldwide, but could be particularly severe to vulnerable wetland environments such as the Everglades. This work investigates the impact global climate change could have on the hydrologic and vegetative makeup of Everglades National Park (ENP) under forecasted emissions scenarios. Using a simple stochastic model of aboveground water levels driven by a fluctuating rainfall input, we link across ENP a location's mean depth and percent time of inundation to the predicted changes in precipitation from climate change. Changes in the hydrologic makeup of ENP are then related to changes in vegetation community composition through the use of relationships developed between two publically available datasets. Results show that under increasing emissions scenarios mean annual precipitation was forecasted to decrease across ENP leading to a marked hydrologic change across the region. Namely, areas were predicted to be shallower in average depth of standing water and inundated less of the time. These hydrologic changes in turn lead to a shift in ENP's vegetative makeup, with xeric vegetative communities becoming more numerous and hydric vegetative communities becoming scarcer. Noticeably, the most widespread of vegetative communities, sawgrass, decreases in abundance under increasing emissions scenarios. These results are an important indicator of the effects climate change may have on the Everglades region and raise important management implications for those seeking to restore this area to its historical hydrologic and vegetative condition.

Survival and growth responses of eight Everglades tree species along an experimental hydrological gradient on two tree island types

Questions: How are the early survival and growth of seedlings of Everglades tree species planted in an experimental setting on artificial tree islands affected by hydrology and substrate type? What are the implications of these responses for broader tree island restoration efforts? Location: Loxahatchee Impoundment Landscape Assessment (LILA), Boynton Beach, Florida, USA. Methods: An experiment was designed to test hydrological and substrate effects on seedling growth and survivorship. Two islands – a peat and a limestone-core island representing two major types found in the Everglades – were constructed in four macrocosms. A mixture of eight tree species was planted on each island in March of 2006 and 2007. Survival and height growth of seedlings planted in 2006 were assessed periodically during the next two and a half years. Results: Survival and growth improved with increasing elevation on both tree island substrate types. Seedlings' survival and growth responses along a moisture gradient matched species distributions along natural hydrological gradients in the Everglades. The effect of substrate on seedling performance showed higher survival of most species on the limestone tree islands, and faster growth on their peat-based counterparts. Conclusions: The present results could have profound implications for restoration of forests on existing landforms and artificial creation of tree islands. Knowledge of species tolerance to flooding and responses to different edaphic conditions present in wetlands is important in selecting suitable species to plant on restored tree islands

The effects of hydroperiod on the life-history parameters of Lucania goodei (fundulidae) in the Florida Everglades

In aquatic ecosystems, hydrological fluctuation may generate a gradient of lifehistory responses associated with marsh drying. This study was conducted in the Florida Everglades to document spatial and temporal variability in growth and survivorship of the bluefin killifish (Lucania goodei) from six populations along a hydroperiod gradient. The otolith-microstructure analysis of field-collected fish was used to estimate growth rate and those data were combined with field-density estimates for survivorship analysis. Otolith analysis revealed that L. goodei is extremely short-lived with no variation in growth rates and very little spatial or temporal variation in survivorship. These results suggest that bluefin killifish populations experience similar life histories across a diversity of hydroperiods either through well-mixed populations homogenizing these vital rates, or more likely, that a multitude of factors force L. goodei to respond to these "stressors" in a similar fashion across hydroperiod gradients.

Integrated sensitivity analysis, calibration, and uncertainty propagation analysis approaches for supporting hydrological modeling

The successful performance of a hydrological model is usually challenged by the quality of the sensitivity analysis, calibration and uncertainty analysis carried out in the modeling exercise and subsequent simulation results. This is especially important under changing climatic conditions where there are more uncertainties associated with climate models and downscaling processes that increase the complexities of the hydrological modeling system. In response to these challenges and to improve the performance of the hydrological models under changing climatic conditions, this research proposed five new methods for supporting hydrological modeling. First, a design of experiment aided sensitivity analysis and parameterization (DOE-SAP) method was proposed to investigate the significant parameters and provide more reliable sensitivity analysis for improving parameterization during hydrological modeling. The better calibration results along with the advanced sensitivity analysis for significant parameters and their interactions were achieved in the case study. Second, a comprehensive uncertainty evaluation scheme was developed to evaluate three uncertainty analysis methods, the sequential uncertainty fitting version 2 (SUFI-2), generalized likelihood uncertainty estimation (GLUE) and Parameter solution (ParaSol) methods. The results showed that the SUFI-2 performed better than the other two methods based on calibration and uncertainty analysis results. The proposed evaluation scheme demonstrated that it is capable of selecting the most suitable uncertainty method for case studies. Third, a novel sequential multi-criteria based calibration and uncertainty analysis (SMC-CUA) method was proposed to improve the efficiency of calibration and uncertainty analysis and control the phenomenon of equifinality. The results showed that the SMC-CUA method was able to provide better uncertainty analysis results with high computational efficiency compared to the SUFI-2 and GLUE methods and control parameter uncertainty and the equifinality effect without sacrificing simulation performance. Fourth, an innovative response based statistical evaluation method (RESEM) was proposed for estimating the uncertainty propagated effects and providing long-term prediction for hydrological responses under changing climatic conditions. By using RESEM, the uncertainty propagated from statistical downscaling to hydrological modeling can be evaluated. Fifth, an integrated simulation-based evaluation system for uncertainty propagation analysis (ISES-UPA) was proposed for investigating the effects and contributions of different uncertainty components to the total propagated uncertainty from statistical downscaling. Using ISES-UPA, the uncertainty from statistical downscaling, uncertainty from hydrological modeling, and the total uncertainty from two uncertainty sources can be compared and quantified. The feasibility of all the methods has been tested using hypothetical and real-world case studies. The proposed methods can also be integrated as a hydrological modeling system to better support hydrological studies under changing climatic conditions. The results from the proposed integrated hydrological modeling system can be used as scientific references for decision makers to reduce the potential risk of damages caused by extreme events for long-term water resource management and planning.

Hydrological and meteorological investigations in a lake near Kangerlussuaq, west Greenland

Few hydrological studies have been made in Greenland, other than on glacial hydrology associated with the ice sheet. Understanding permafrost hydrology and hydroclimatic change and variability, however, provides key information for understanding climate change effects and feedbacks in the Arctic landscape. This paper presents a new extensive and detailed hydrological and meteorological open access dataset, with high temporal resolution from a 1.56 km**2 permafrost catchment with a lake underlain by a through talik close to the ice sheet in the Kangerlussuaq region, western Greenland. The paper describes the hydrological site investigations and utilized equipment, as well as the data collection and processing. The investigations were performed between 2010 and 2013. The high spatial resolution, within the investigated area, of the dataset makes it highly suitable for various detailed hydrological and ecological studies on catchment scale.