Pan evaporation modelling and changing attribution analysis on the Tibetan Plateau (1970–2012)

Pan evaporation (E_p) is an important indicator of water and energy and the decline of E_p has been reported in many regions over the last decades. The climate and E_p are dependent on each other. In this study, the temporal trends of E_p and main E_p drivers, namely mean air temperature (T_a), wind speed (u), global solar radiation (R_s), net long‐wave radiation(R_nl) and vapour pressure deficit (D) from 1970 to 2012, were calculated on the basis of 26 meteorological stations on the Tibetan Plateau. The arithmetic average of E_p from 26 stations decreased with the rate of ?11.91 mm a^?2; the trends of R_s, R_nl, T_a, u and D were ?1.434 w m^?2 decade^?1, 0.2511 w m^?2 decade^?1, 0.3590°C decade^?1, ?0.2376 m s^?1 decade^?1 and 9.523 Pa decade^?1, respectively. The diffuse irradiance is an essential parameter to model E_p and quantify the contribution of climatic factors to changing E_p. 60 724 observations of R_s and diffuse solar irradiance (R_d) from seven of the 26 stations were used to develop the correlation between the diffuse fraction (R_d/R_s), and the clearness index (R_s/R_o). On the basis of the estimation of the diffuse component of R_s and climatic data, we modified the PenPan model to estimate Chinese micro‐pan evaporation (E_p) and assess the attribution of E_p dynamics using partial derivatives. The results showed that there was a good agreement between the observed and calculated daily E_p values. The observed decrease in E_p was mostly due to declining wind speed (?13.7 mm a^?2) with some contributions from decreasing solar irradiance (?3.1 mm a^?2); and the increase of temperature had a large positive effect (4.55 mm a^?2) in total whilst the increase of R_nl had insignificant effect (0.35 mm a^?2) on E_p rates. The change of E_p is the net result of all the climatic variables. Copyright © 2014 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.     

Assessing sensitivity of hydrologic responses to climate change from forested watershed in Mississippi

The climatic processes such as changes in precipitation, temperature and atmospheric CO₂ concentration can intensify the effects on water resources. An assessment of the effects of long‐term climate change on water resources is essential to the development of water quality improvement programs. This study was conducted in the Upper Pearl River Watershed (UPRW) in east‐central Mississippi to assess the effects of long‐term potential future climate change on average mean monthly stream flow from the five spatially distributed U. S. Geological Survey (USGS) gage stations in the UPRW using the Soil and Water Assessment Tool. The model was calibrated (January 1981 to December 1994) and validated (January 1995 to September 2008) using monthly measured stream flow data. The calibrated and validated model determined good to very good performance for stream flow prediction (R² and E from 0·60 to 0·86) between measured and predicted stream flow values. The root mean square error values (from 14 to 37 m³ s^?1) were estimated at similar levels of errors during model calibration and validation. The results showed that long‐term (50 years) average monthly stream flow sensitivity due to climate change effects was found the greatest as a result of percentage change in the precipitation followed by carbon dioxide (CO₂) concentration and temperature. The long‐term model simulation scenarios as compared with the base scenario for all five spatially distributed USGS gage stations in the UPRW estimated an average monthly stream flow decrease (from 54 to 67%) and average monthly stream flow increase (from 67 to 79%) depending on the spatial characteristics of the USGS gage stations. Overall, the results indicate that the UPRW hydrology is very sensitive to potential future climate changes and that these changes could stimulate increased streamflow generation from the watershed. Copyright © 2010 John Wiley & Sons, Ltd.     

Modelling snowpack surface temperature in the Canadian Prairies using simplified heat flow models

Three practical schemes for computing the snow surface temperature T_s, i.e. the force–restore method (FRM), the surface conductance method (SCM), and the Kondo and Yamazaki method (KYM), were assessed with respect to T_s retrieved from cloud‐free, NOAA‐AVHRR satellite data for three land‐cover types of the Paddle River basin of central Alberta. In terms of R², the mean T_s, the t‐test and F‐test, the FRM generally simulated more accurate T_s than the SCM and KYM. The bias in simulated T_s is usually within several degrees Celsius of the NOAA‐AVHRR T_s for both the calibration and validation periods, but larger errors are encountered occasionally, especially when T_s is substantially above 0 °C. Results show that the simulated T_s of the FRM is more consistent than that of the SCM, which in turn was more consistent than that of the KYM. This is partly because the FRM considers two aspects of heat conduction into snow, a stationary‐mean diurnal (sinusoidal) temperature variation at the surface coupled to a near steady‐state ground heat flux, whereas the SCM assumes a near steady‐state, simple heat conduction, and other simplifying assumptions, and the KYM does not balance the snowpack heat fluxes by assuming the snowpack having a vertical temperature profile that is linear. Copyright © 2005 John Wiley & Sons, Ltd.     

A model to predict stream water temperature across the conterminous USA

Stream water temperature (t_s) is a critical water quality parameter for aquatic ecosystems. However, t_s records are sparse or nonexistent in many river systems. In this work, we present an empirical model to predict t_s at the site scale across the USA. The model, derived using data from 171 reference sites selected from the Geospatial Attributes of Gages for Evaluating Streamflow database, describes the linear relationship between monthly mean air temperature (t_a) and t_s. Multiple linear regression models are used to predict the slope (m) and intercept (b) of the t_a–t_s linear relation as a function of climatic, hydrologic and land cover characteristics. Model performance to predict t_s resulted in a mean Nash–Sutcliffe efficiency coefficient of 0.78 across all sites. Application of the model to predict t_s at additional 89 nonreference sites with a higher human alteration yielded a mean Nash–Sutcliffe value of 0.45. We also analysed seasonal thermal sensitivity (m) and found strong hysteresis in the t_a–t_s relation. Drainage area exerts a strong control on m in all seasons, whereas the cooling effect of groundwater was only evident for the spring and fall seasons. However, groundwater contributions are negatively related to mean t_s in all seasons. Finally, we found that elevation and mean basin slope are negatively related to mean t_s in all seasons, indicating that steep basins tend to stay cooler because of shorter residence times to gain heat from their surroundings. This model can potentially be used to predict climate change impacts on t_s across the USA. Copyright © 2014 John Wiley & Sons, Ltd.     

Seasonal climate patterns and their influence on calibration of the Hargreaves-Samani equation

Abstract

Annual patterns in climate parameters were studied to evaluate how these influence the quality of reference evapotranspiration (ETo) estimates obtained from the Hargreaves-Samani (HS) equation, since the method only uses the measured temperature directly. The work evaluates how these patterns can be used to improve the HS ETo estimates. Ten-year moving averages from a set of California Irrigation Management Information System (CIMIS) stations were used to evaluate the relationships between solar radiation (R_s), temperature (T) and ETo. The results indicate that T treads behind solar radiation and its value peaks some 25 days later. Thus, the main irrigation season in the Mediterranean climate (1 May–30 September) can be divided into three phases: increasing R_s and T; decreasing R_s with increasing T; and decreasing R_s and T. Non-univocal annual cycles were observed between R_s and T, ETo and R_s, and ETo and T. These annual patterns result in important seasonal changes in the ratio between the HS and Penman-Monteith (FAO PM) ETo estimates. The changes are particularly important during the irrigation season, where the FAO PM initially calculates greater ETo values than the HS methodology, and from the end of May to early September, where the HS equation overestimates the ETo values (by 17 mm, or 3%). These patterns obtained from 2000–2009 data were used to calibrate and improve HS ETo estimates at new sites for the 2010–2011 period. Calibration based on the proposed seasonal region-wide FAO PM/HS ETo ratios improved both the bias (decreased from 0.40 to 0.36 mm d^-1) and r² (increased from 0.67 to 0.87) of the ETo estimates for the irrigation season. The proposed methodology can be easily applied to other regions, even when the existing weather stations are sparse.

Editor Z.W. Kundzewicz     

Reference evapotranspiration trends and their sensitivity to climatic change on the Tibetan Plateau (1970–2009)

Evapotranspiration is an important component of the water and energy balance. It is dependent on climate. Precipitation, solar radiation, temperature, humidity, and wind all contribute to the rate of evapotranspiration. In this study, the temporal trends of reference evapotranspiration (ET_ref) and four main ET_ref drivers, namely, mean air temperature (T_a), wind speed (u₂), net radiation (R_n) and actual vapour pressure (e_a) from 1970 to 2009, were calculated based on 75 meteorological stations on the Tibetan Plateau. The results showed that the ET_ref on the Tibetan Plateau decreased on average by 0.6909 mm a^‐1a^‐1 from 1970 to 2009. T_a and e_a showed an increasing trend, whereas u₂ and R_n exhibited a decreasing trend. To explore the underlying causes of the ET_ref variation, an attribution analysis was performed to quantify the contribution of T_a, u₂, R_n and e_a, which showed that the changes in u₂, R_n and e_a produced the negative effect, whereas T_a produced the positive effect on ET_ref rates. The changes in u₂ were found to produce the largest decrease (?0.7 mm) in ET_ref, followed by e_a (?0.4 mm) and R_n (?0.1 mm). Although the significant increase in T_a had a large positive effect (0.51 mm) on ET_ref rates, changes in the other three variables each reduced ET_ref rates, resulting in an overall negative trend in ET_ref. Copyright © 2012 John Wiley & Sons, Ltd.     

Performance evaluation of satellite-based approaches for the estimation of daily air temperature and reference evapotranspiration

Different satellite-based radiation (Makkink) and temperature (Hargreaves-Samani, Penman-Monteith temperature, PMT) reference evapotranspiration (ET_o) models were compared with the FAO56-PM method over the Cauvery basin, India. Maximum air temperature (T_max) required in the ET_o models was estimated using the temperature–vegetation index (TVX) and an advanced statistical approach (ASA), and evaluated with observed T_max obtained from automatic weather stations. Minimum air temperature (T_min) was estimated using ASA. Land surface temperature was employed in the ET_o models in place of air temperature (T_a) to check the potency of its applicability. The results suggest that the PMT model with T_a as input performed better than the other ET_o models, with correlation coefficient (r), averaged root mean square error (RMSE) and mean bias error (MBE) of 0.77, 0.80 mm d^?1 and ?0.69 for all land cover classes. The ASA yielded better T_max and T_min values (r and RMSE of 0.87 and 2.17°C, and 0.87 and 2.27°C, respectively).     

Hydrological responses to defoliation and drought of an upland oak/pine forest

Hydrologic variability during 2005–2011 was observed and analyzed at an upland oak/pine forest in the New Jersey Pinelands. The forest experienced defoliation by Gypsy moth (Lymantria dispar L.) in 2007, drought conditions in 2006 and a more severe drought in 2010. By using sap flux and eddy covariance measurements, stream discharge data from USGS, soil water changes, precipitation (P) and precipitation throughfall, a local water balance was derived. Average annual canopy transpiration (E_C) during 2005–2011 was 201 mm a^?1 ± 47 mm a^?1. A defoliation event reduced E_C by 20% in 2007 compared with the 2005–2011 mean. During drought years in 2006 and 2010, stand transpiration was reduced by 8% in July 2006 and by 18% in 2010, respectively, compared with the overall July average. During July 2007, after the defoliation and subsequent reflushing of half of the leaves, E_C was reduced by 25%. This stand may experience higher sensitivity to drought when recovering from a defoliation event as evidenced by the higher reduction of E_C in 2010 (post‐defoliation) compared with 2006 (pre‐defoliation). Stream water discharge was normalized to the watershed area by dividing outflow with the watershed area. It showed the greatest correlation with transpiration for time lags of 24 days and 219 days, suggesting hydrological connectivity on the watershed scale; stream water discharge increases when transpiration decreases, coinciding with leaf‐on and leaf‐off conditions. Thus, any changes in transpiration or precipitation will also alter stream water discharge and therefore water availability. Under future climate change, frequency and intensity of precipitation and episodic defoliation events may alter local water balance components in this upland oak/pine forest. Copyright © 2013 John Wiley & Sons, Ltd.     

A multicatchment analysis of headwater and downstream temperature effects from contemporary forest harvesting

Stream temperature is a key physical water‐quality parameter, controlling many biological, chemical, and physical processes in aquatic ecosystems. Maintenance of cool stream temperatures during summer is critical for high‐quality aquatic habitat. As such, transmission of warm water from small, nonfish‐bearing headwater streams after forest harvesting could cause warming in downstream fish‐bearing stream reaches with negative consequences. In this study, we evaluate (a) the effects of contemporary forest management practices on stream temperature in small, headwater streams, (b) the transmission of thermal signals from headwater reaches after harvesting to downstream fish‐bearing reaches, and (c) the relative role of lithology and forest management practices in influencing differential thermal responses in both the headwater and downstream reaches. We measured summer stream temperatures both preharvest and postharvest at 29 sites—12 upstream sites (4 reference, 8 harvested) and 17 downstream sites (5 reference, 12 harvested)—across 3 paired watershed studies in western Oregon. The 7‐day moving average of daily maximum stream temperature (T_7DAYMAX) was greater during the postharvest period relative to the preharvest period at 7 of the 8 harvested upstream sites. Although the T_7DAYMAX was generally warmer in the downstream direction at most of the stream reaches during both the preharvest and postharvest period, there was no evidence for additional downstream warming related to the harvesting activity. Rather, the T_7DAYMAX cooled rapidly as stream water flowed into forested reaches ~370–1,420 m downstream of harvested areas. Finally, the magnitude of effects of contemporary forest management practices on stream temperature increased with the proportion of catchment underlain by more resistant lithology at both the headwater and downstream sites, reducing the potential for the cooling influence of groundwater.     

Temperature in lowland Danish streams: contemporary patterns,empirical models and future scenarios

Continuous temperature measurements at 11 stream sites in small lowland streams of North Zealand, Denmark over a year showed much higher summer temperatures and lower winter temperatures along the course of the stream with artificial lakes than in the stream without lakes. The influence of lakes was even more prominent in the comparisons of colder lake inlets and warmer outlets and led to the decline of cold‐water and oxygen‐demanding brown trout. Seasonal and daily temperature variations were, as anticipated, dampened by forest cover, groundwater input, input from sewage plants and high downstream discharges. Seasonal variations in daily water temperature could be predicted with high accuracy at all sites by a linear air‐water regression model (r²: 0·903–0·947). The predictions improved in all instances (r²: 0·927–0·964) by a non‐linear logistic regression according to which water temperatures do not fall below freezing and they increase less steeply than air temperatures at high temperatures because of enhanced heat loss from the stream by evaporation and back radiation. The predictions improved slightly (r²: 0·933–0·969) by a multiple regression model which, in addition to air temperature as the main predictor, included solar radiation at un‐shaded sites, relative humidity, precipitation and discharge. Application of the non‐linear logistic model for a warming scenario of 4–5 °C higher air temperatures in Denmark in 2070‐2100 yielded predictions of temperatures rising 1·6–3·0 °C during winter and summer and 4·4–6·0 °C during spring in un‐shaded streams with low groundwater input. Groundwater‐fed springs are expected to follow the increase of mean air temperatures for the region. Great caution should be exercised in these temperature projections because global and regional climate scenarios remain open to discussion. Copyright © 2006 John Wiley & Sons, Ltd.     

Integrating downscaled CMIP5 data with a physically based hydrologic model to estimate potential climate change impacts on streamflow processes in a mixed‐use watershed

Climatic changes have altered surface water regimes worldwide, and climate projections suggest that such alterations will continue. To inform management decisions, climate projections must be paired with hydrologic models to develop quantitative estimates of watershed scale water regime changes. Such modeling approaches often involve downscaling climate model outputs, which are generally presented at coarse spatial scales. In this study, Coupled Model Intercomparison Project Phase 5 climate model projections were analyzed to determine models representing severe and conservative climate scenarios for the study watershed. Based on temperature and precipitation projections, output from GFDL‐ESM2G (representative concentration pathway 2.6) and MIROC‐ESM (representative concentration pathway 8.5) were selected to represent conservative (Δ_C) and severe (Δ_S) change scenarios, respectively. Climate data were used as forcing for the soil and water assessment tool to analyze the potential effects of climate change on hydrologic processes in a mixed‐use watershed in central Missouri, USA. Results showed annual streamflow decreases ranging from ?5.9% to ?26.8% and evapotranspiration (ET) increases ranging from +7.2% to +19.4%. During the mid‐21st century, sizeable decreases to summer streamflow were observed under both scenarios, along with large increases of fall, spring, and summer ET under Δ_S. During the late 21st century period, large decreases of summer streamflow under both scenarios, and large increases to spring (Δ_S), fall (Δ_S) and summer (Δ_C) ET were observed. This study demonstrated the sensitivity of a Midwestern watershed to future climatic changes utilizing projections from Coupled Model Intercomparison Project Phase 5 models and presented an approach that used multiple climate model outputs to characterize potential watershed scale climate impacts.     

Quantifying and modelling urban stream temperature: a central US watershed study

Hydrologic models that rely on site specific linear and non‐linear regression water temperature (T_w) subroutines forced solely with observed air temperature (T_a) may not accurately estimate T_w in mixed‐use urbanizing watersheds where hydrogeological and land use complexity may confound common T_w regime assumptions. A nested‐scale experimental watershed study design was used to test T_w model predictions in a representative mixed‐use urbanizing watershed of the central USA. The linear regression T_w model used in the Soil and Water Assessment Tool (SWAT), a non‐linear regression T_w model, and a process‐based T_w model that accounts for watershed hydrology were evaluated. The non‐linear regression T_w model tested at a daily time step performed significantly (P < 0.01) better than the linear T_w model currently used in SWAT. Both regression T_w models overestimated T_w in lower temperature ranges (T_w < 10.0 °C) with percent bias (PBIAS) values ranging from ?28.2% (non‐linear T_w model) to ?66.1% (linear regression T_w model) and underestimated T_w in the higher temperature range (T_w > 25.0 °C) by 3.2%, and 7.2%, respectively. Conversely, the process‐based T_w model closely estimated T_w in lower temperature ranges (PBIAS = 4.5%) and only slightly underestimated T_w in the higher temperature range (PBIAS = 1.7%). Findings illustrate the benefit of integrating process‐based T_w models with hydrologic models to improve model transferability and T_w predictive confidence in urban mixed‐land use watersheds. The findings in this work are distinct geographically and in terms of mixed‐land use complexity and are therefore of immediate value to land‐use managers in similarly urbanizing watersheds globally. Copyright © 2015 John Wiley & Sons, Ltd.     

Five‐Year Soil Respiration Reflected Soil Quality Evolution in Different Forest and Grassland Vegetation Types in the Eastern Loess Plateau of China

Soil CO₂ efflux in forest and grassland over 5 years from 2005 to 2009 in a semiarid mountain area of the Loess plateau, China, was measured. The aim was to compare the soil respiration and its annual and inter‐annual responses to the changes in soil temperature and soil water content between the two vegetation types for observing soil quality evolution. The differences among the five study years were the annual precipitation (320.1, 370.5, 508.8, 341.6, and 567.4 mm in 2005–2009, respectively) and annual distribution. The results showed that the seasonal change of soil respiration in both vegetation types was similar and controlled by soil temperature and soil water content. The mean soil respiration across 5 years in the forest (3.78 ± 2.68 µmol CO₂ m^?2 s^?1) was less than that in the grassland (4.04 ± 3.06 µmol CO₂ m^?2 s^?1), and the difference was significant. The drought soil in summer depressed soil respiration substantially. The Q₁₀ value across 5‐year measurements was 2.89 and 2.94 for forest and grassland. When soil water content was between wilting point (WP) and field capacity (FC), the Q₁₀ in both types increased with increasing soil water content, and when soil water content dropped to below WP, soil respiration and the Q₁₀ decreased substantially. Although an exponential model was well fitted to predict the annual mean soil respiration for each single year data, it overestimated and underestimated soil respiration, respectively, in drought conditions and after rain for short periods of time during the year. The two‐variable models including temperature and water content variables could be well used to predict soil respiration for both types in all weather conditions. The models proposed are useful for understanding and predicting potential changes in the eastern part of Loess plateau in response to climate change.     

Predicting landscape sensitivity to present and future floods in the Pacific Northwest,USA

Floods are the most frequent natural disaster, causing more loss of life and property than any other in the USA. Floods also strongly influence the structure and function of watersheds, stream channels, and aquatic ecosystems. The Pacific Northwest is particularly vulnerable to climatically driven changes in flood frequency and magnitude, because snowpacks that strongly influence flood generation are near the freezing point and thus sensitive to small changes in temperature. To improve predictions of future flooding potential and inform strategies to adapt to these changes, we mapped the sensitivity of landscapes to changes in peak flows due to climate warming across Oregon and Washington. We first developed principal component‐based models for predicting peak flows across a range of recurrence intervals (2‐, 10‐, 25‐, 50‐, and 100‐years) based on historical instantaneous peak flow data from 1000 gauged watersheds in Oregon and Washington. Key predictors of peak flows included drainage area and principal component scores for climate, land cover, soil, and topographic metrics. We then used these regression models to predict future peak flows by perturbing the climate variables based on future climate projections (2020s, 2040s, and 2080s) for the A1B emission scenario. For each recurrence interval, peak flow sensitivities were computed as the ratio of future to current peak flow magnitudes. Our analysis suggests that temperature‐induced changes in snowpack dynamics will result in large (>30–40%) increases in peak flow magnitude in some areas, principally the Cascades, Olympics, and Blue Mountains and parts of the western edge of the Rocky Mountains. Flood generation processes in lower elevation areas are less likely to be affected, but some of these areas may be impacted by floodwaters from upstream. These results can assist land, water, and infrastructure managers in identifying watersheds and resources that are particularly vulnerable to increased peak flows and developing plans to increase their resilience. Copyright © 2015 John Wiley & Sons, Ltd.     

Characterizing stream temperature hysteresis in forested headwater streams

Stream temperature (T_s) is a key water quality parameter that controls several biological, ecological, and chemical processes in aquatic systems. In forested headwaters, exchanges of energy across air-water-streambed interfaces may influence T_s regimes, especially during storm events as the sources of runoff change over space and time. Analysis of the hysteretic behaviour of T_s during storm events may provide insights into rainfall-runoff responses, but such relationships have not been thoroughly investigated. As such, our objectives were to (a) quantify the variability of stream temperature hysteresis across seasons in different sub-regions and (b) investigate the relationship between the hysteretic response and catchment characteristics. T_s hysteresis during storm events was assessed based on the hysteresis index (HI), which describes the directionality of hysteresis loops, and the temperature response index (TRI), which indicates whether T_s increased or decreased during a storm event. We analysed T_s data from 10 forested headwater reaches in two sub-regions (McGarvey and West Fork Tectah) in Northern California. We also performed a clustering analysis to examine the relationship amongst HI, TRI, topographic metrics, and meteorological characteristics of the study areas. Overall, the hysteretic behaviour of T_s varied across seasons—the greatest HI occurred during spring and summer. Interestingly, in the McGarvey streams the variability in T_s hysteresis co-varied strongly with topographic metrics (i.e., upslope accumulative area, average channel slope, topographic wetness index). Comparatively, in West Fork Tectah the variability of T_s hysteresis co-varied most strongly with meteorological metrics (i.e., antecedent rainfall events, solar radiation, and air temperature). Variables such as the gradient between stream and air temperatures, slope, and wetted width were significant for both sub-regional hysteretic patterns. We posit that the drivers of T_s response during storms are likely dependent on catchment physiographic characteristics. Our study also illustrated the potential utility of stream temperature as a tracer for improving the understanding of hydrologic connectivity and shifts in the dominant runoff contributions to streamflow during storm events.     

Groundwater contamination risks from conservative point source pollutants in a future climate

ABSTRACT

The groundwater contamination risk in future climates was investigated at three locations in Sweden. Solute transport penetration depths were simulated using the HYDRUS-1D model using historical data and an ensemble of climate projections including two global climate models (GCMs), three emission scenarios and one regional climate model. Most projections indicated increasing precipitation and evapotranspiration until mid-century with a further increase at end-century. Results showed both increasing and decreasing groundwater contamination risks depending on emission scenario and GCM. Generally, the groundwater contamination risk is likely to be unchanged until mid-century, but higher at the end of the century. Soil and site specific relationships between Δ(P – PET) (i.e. change in the difference between precipitation, P, and potential evapotranspiration, PET) and changes in solute transport depths were determined. Using this, changes in solute transport depths for other climate projections can be assessed.     

Assessment of future groundwater recharge in semi‐arid regions under climate change scenarios (Serral‐Salinas aquifer,SE Spain). Could increased rainfall variability increase the recharge rate?

The projected impact of climate change on groundwater recharge is a challenge in hydrogeological research because substantial doubts still remain, particularly in arid and semi‐arid zones. We present a methodology to generate future groundwater recharge scenarios using available information about regional climate change projections developed in European Projects. It involves an analysis of regional climate model (RCM) simulations and a proposal for ensemble models to assess the impacts of climate change. Future rainfall and temperature series are generated by modifying the mean and standard deviation of the historical series in accordance with estimates of their change provoked by climate change. Future recharge series will be obtained by simulating these new series within a continuous balance model of the aquifer. The proposed method is applied to the Serral‐Salinas aquifer, located in a semi‐arid zone of south‐east Spain. The results show important differences depending on the RCM used. Differences are also observed between the series generated by imposing only the changes in means or also in standard deviations. An increase in rainfall variability, as expected under future scenarios, could increase recharge rates for a given mean rainfall because the number of extreme events increases. For some RCMs, the simulations predict total recharge increases over the historical values, even though climate change would produce a reduction in the mean rainfall and an increased mean temperature. A method based on a multi‐objective analysis is proposed to provide ensemble predictions that give more value to the information obtained from the best calibrated models. The ensemble of predictions estimates a reduction in mean annual recharge of 14% for scenario A2 and 58% for scenario A1B. Lower values of future recharge are obtained if only the change in the mean is imposed. Copyright © 2014 John Wiley & Sons, Ltd.     

Verification of land surface evapotranspiration estimation from remote sensing spatial contextual information

Estimation of evapotranspiration (ET) is of great significance in modeling the water and energy interactions between land and atmosphere. Negative correlation of surface temperature (T_s) versus vegetation index (VI) from remote sensing data provides diagnosis on the spatial pattern of surface soil moisture and ET. This study further examined the applicability of T_s–VI triangle method with a newly developed edges determination technique in estimating regional evaporative fraction (EF) and ET at MODIS pixel scale through comparison with large aperture scintillometer (LAS) and high‐level eddy covariance measurements collected at Changwu agro‐ecological experiment station from late June to late October, 2009. An algorithm with merely land and atmosphere products from MODIS onboard Terra satellite was used to estimate the surface net radiation (R_n) and soil heat flux. In most cases, the estimated instantaneous R_n was in good agreement with surface measurement with slight overestimation by 12 W/m². Validation results from LAS measurement showed that the root mean square error is 0.097 for instantaneous EF, 48 W/m² for instantaneous sensible heat flux, and 30 W/m² for daily latent heat flux. This paper successfully presents a miniature of the overall capability of T_s–VI triangle in estimating regional EF and ET from limited number of data. For a thorough interpretation, further comprehensive investigation needs to be done with more integration of remote sensing data and in‐situ surface measurements. Copyright © 2011 John Wiley & Sons, Ltd.     

Evaluation of the change in dominant periods in the lake-bed zone of Mexico City produced by ground subsidence through the use of site amplification factors

We compute site amplification functions for several sites in Mexico City using actual accelerograms recorded from 1985 to 2010 and we present field evidence of the change in the dominant period of a given site (T_s) as a consequence of ground subsidence produced by groundwater withdrawal. The changes in T_s are larger in the lake-bed zone where thicker clay deposits exist, although there are sites in the southwest part of the lake-bed zone where T_s has remained constant. With the information obtained from the site amplification functions and available geotechnical soundings we develop an empirical model to estimate the future value of T_s for several sites in Mexico City. Because the practical application of the model requires extrapolation we also present a method to compute the uncertainty of the model when it is used to forecast a future value of T_s at a given site. Our results suggest that significant changes in the dominant period at several sites in Mexico City can be expected in the future.