Simulation of the hydrological impacts of climate change on a restored floodplain

Thirty UK Climate Projections 2009 (UKCP09) scenarios are simulated using a MIKE SHE/MIKE 11 model of a restored floodplain in eastern England. Annual precipitation exhibits uncertainty in direction of change. Extreme changes (10 and 90% probability) range between ?27 and +30%. The central probability projects small declines (相似文献   

Assessing the effect of climate natural variability in water resources evaluation impacted by climate change

Water resource assessment on climate change is crucial in water resource planning and management. This issue is becoming more urgent with climate change intensifying. In the current research of climate change impact, climate natural variability (fluctuation) has seldom been studied separately. Many studies keep attributing all changes (e.g. runoff) to climate change, which may lead to wrong understanding of climate change impact assessment. Because of lack of long enough historical series, impacts of climate variability have been always avoided deliberately. Based on Latin hypercube sampling technique, a block sampling approach was proposed for climate variability simulation in this study. The widely used time horizon (1961–1991) was defined as baseline period, and the runoff variation probability affected by climate natural variability was analysed. Allowing for seven future climate projections in total of three GCMs (CSIRO, NCAR, and MPI) and three emission scenarios (A1B, A2, and B1), the impact of future climate change on water resources was estimated in terms of separating the contribution from climate natural variability. Based on the analysis of baseline period, for the future period from 2021 to 2051, the impact of climate natural variability may play a major part, whereas for the period from 2061 to 2091, climate change attributed to greenhouse gases may dominate the changing process. The results show that changes from climate variability possess a comparable magnitude, which highlights the importance to separate impacts of climate variability in assessing climate change, instead of attributing all changes to climate change solely. Copyright © 2012 John Wiley & Sons, Ltd.     

How do hydrologic modeling decisions affect the portrayal of climate change impacts?

End users face a range of subjective decisions when evaluating climate change impacts on hydrology, but the importance of these decisions is rarely assessed. In this paper, we evaluate the implications of hydrologic modelling choices on projected changes in the annual water balance, monthly simulated processes, and signature measures (i.e. metrics that quantify characteristics of the hydrologic catchment response) under a future climate scenario. To this end, we compare hydrologic changes computed with four different model structures – whose parameters have been obtained using a common calibration strategy – with hydrologic changes computed with a single model structure and parameter sets from multiple options for different calibration decisions (objective function, local optima, and calibration forcing dataset). Results show that both model structure selection and the parameter estimation strategy affect the direction and magnitude of projected changes in the annual water balance, and that the relative effects of these decisions are basin dependent. The analysis of monthly changes illustrates that parameter estimation strategies can provide similar or larger uncertainties in simulations of some hydrologic processes when compared with uncertainties coming from model choice. We found that the relative effects of modelling decisions on projected changes in catchment behaviour depend on the signature measure analysed. Furthermore, parameter sets with similar performance, but located in different regions of the parameter space, provide very different projections for future catchment behaviour. More generally, the results obtained in this study prompt the need to incorporate parametric uncertainty in multi‐model frameworks to avoid an over‐confident portrayal of climate change impacts. Copyright © 2015 John Wiley & Sons, Ltd.     

Spatial uncertainty in bias corrected climate change projections and hydrogeological impacts

The question of which climate model bias correction methods and spatial scales for correction are optimal for both projecting future hydrological changes as well as removing initial model bias has so far received little attention. For 11 climate models (CMs), or GCM/RCM – Global/Regional Climate Model pairing, this paper analyses the relationship between complexity and robustness of three distribution‐based scaling (DBS) bias correction methods applied to daily precipitation at various spatial scales. Hydrological simulations are forced by CM inputs to assess the spatial uncertainty of groundwater head and stream discharge given the various DBS methods. A unique metric is devised, which allows for comparison of spatial variability in climate model bias and projected change in precipitation. It is found that the spatial variability in climate model bias is larger than in the climate change signals. The magnitude of spatial bias seen in precipitation inputs does not necessarily correspond to the magnitude of biases seen in hydrological outputs. Variables that integrate basin responses over time and space are more sensitive to mean spatial biases and less so on extremes. Hydrological simulations forced by the least parameterized DBS approach show the highest error in mean and maximum groundwater heads; however, the most highly parameterised DBS approach shows less robustness in future periods compared with the reference period it was trained in. For hydrological impacts studies, choice of bias correction method should depend on the spatial scale at which hydrological impacts variables are required and whether CM initial bias is spatially uniform or spatially varying. Copyright © 2015 John Wiley & Sons, Ltd.     

Macroscale hydrological modelling approach for study of large scale hydrologic impacts under climate change in Indian river basins

In climate‐change studies, a macroscale hydrologic model (MHM) operating over large scales can be an important tool in developing consistent hydrological variability estimates over large basins. MHMs, which can operate at coarse grid resolutions of about 1° latitude by longitude, have been used previously to study climate change impacts on the hydrology of continental scale or global river basins. They can provide a connection between global atmospheric models and water resource systems on large spatial scales and long timescales. In this study, the variable infiltration capacity (VIC) MHM is used to study large scale hydrologic impacts of climate change for Indian river basins. Large‐scale changes in runoff, evapotranspiration and soil moisture for India, as well as station‐scale changes in discharges for three major river basins with distinct climatic and geographic characteristics are examined in this study. Climate model projections for meteorological variables (precipitation, temperature and wind speed) from three general circulation models (GCMs) and three emissions scenarios are used to drive the VIC MHM. GCM projections are first interpolated to a 1° by 1° hydrologic model grid and then bias‐corrected using a quantile–quantile mapping. The VIC model is able to reproduce observed statistics for discharges in the Ganga, Narmada and Krishna basins reasonably well, even at the coarse grid resolution employed using a calibration period for years 1965–1970 and testing period from 1971–1973/1974. An increasing trend is projected for summer monsoon surface runoff, evapotranspiration and soil moisture in most central Indian river basins, whereas a decrease in runoff and soil moisture is projected for some regions in southern India, with important differences arising from GCM and scenario variability. Discharge statistics show increases in mid‐flow and low flow at Farakka station on Ganga River, increased high flows at Jamtara station upstream of Narmada, and increased high, mid‐flow and low flow for Vijayawada station on Krishna River in the future. Copyright © 2013 John Wiley & Sons, Ltd.     

Using response surfaces to estimate impacts of climate change on flood peaks: assessment of uncertainty

The potential impacts of climate change are an increasing focus of research, and ever‐larger climate projection ensembles are available, making standard impact assessments more onerous. An alternative way of estimating impacts involves response surfaces, which present the change in a given indicator for a large number of plausible climatic changes defined on a regular sensitivity domain. Sets of climate change projections can then be overlaid on the response surface and impacts estimated from the nearest corresponding points of the sensitivity domain, providing a powerful method for fast impact estimation for multiple projections and locations. However, the effect of assumptions necessary for initial response surface development must be assessed. This paper assesses the uncertainty introduced by use of a sensitivity framework for estimating changes in 20‐year return period flood peaks in Britain. This sensitivity domain involves mean annual and seasonal precipitation changes, and a number of simplifications were necessary for consistency and to reduce dimensionality. The effect of these is investigated for nine catchments across Britain, representing nine typical response surfaces (response types), using three sets of climate projections. The results show that catchments can have different causes of uncertainty and some catchments have an overall higher level of uncertainty than others. These differences are compatible with the underlying climatological and hydrological differences between the response types, giving confidence in generalization of the results. This enables the development of uncertainty allowances by response type, to be used alongside the response surfaces to provide more robust impact estimates. Copyright © 2013 John Wiley & Sons, Ltd.     

Modelling climate and land-use change impacts with SWIM: lessons learnt from multiple applications

Abstract

The Soil and Water Integrated Model (SWIM) is a continuous-time semi-distributed ecohydrological model, integrating hydrological processes, vegetation, nutrients and erosion. It was developed for impact assessment at the river basin scale. SWIM is coupled to GIS and has modest data requirements. During the last decade SWIM was extensively tested in mesoscale and large catchments for hydrological processes (discharge, groundwater), nutrients, extreme events (floods and low flows), crop yield and erosion. Several modules were developed further (wetlands and snow dynamics) or introduced (glaciers, reservoirs). After validation, SWIM can be applied for impact assessment. Four exemplary studies are presented here, and several questions important to the impact modelling community are discussed. For which processes and areas can the model be used? Where are the limits in model application? How to apply the model in data-poor situations or in ungauged basins? How to use the model in basins subject to strong anthropogenic pressure?

Editor D. Koutsoyiannis; Associate editor C. Perrin     

Using raw regional climate model outputs for quantifying climate change impacts on hydrology

General circulation model outputs are rarely used directly for quantifying climate change impacts on hydrology, due to their coarse resolution and inherent bias. Bias correction methods are usually applied to correct the statistical deviations of climate model outputs from the observed data. However, the use of bias correction methods for impact studies is often disputable, due to the lack of physical basis and the bias nonstationarity of climate model outputs. With the improvement in model resolution and reliability, it is now possible to investigate the direct use of regional climate model (RCM) outputs for impact studies. This study proposes an approach to use RCM simulations directly for quantifying the hydrological impacts of climate change over North America. With this method, a hydrological model (HSAMI) is specifically calibrated using the RCM simulations at the recent past period. The change in hydrological regimes for a future period (2041–2065) over the reference (1971–1995), simulated using bias‐corrected and nonbias‐corrected simulations, is compared using mean flow, spring high flow, and summer–autumn low flow as indicators. Three RCMs driven by three different general circulation models are used to investigate the uncertainty of hydrological simulations associated with the choice of a bias‐corrected or nonbias‐corrected RCM simulation. The results indicate that the uncertainty envelope is generally watershed and indicator dependent. It is difficult to draw a firm conclusion about whether one method is better than the other. In other words, the bias correction method could bring further uncertainty to future hydrological simulations, in addition to uncertainty related to the choice of a bias correction method. This implies that the nonbias‐corrected results should be provided to end users along with the bias‐corrected ones, along with a detailed explanation of the bias correction procedure. This information would be especially helpful to assist end users in making the most informed decisions.     

Regional impacts of climate change on irrigation water demands

This paper presents an approach to model the expected impacts of climate change on irrigation water demand in a reservoir command area. A statistical downscaling model and an evapotranspiration model are used with a general circulation model (GCM) output to predict the anticipated change in the monthly irrigation water requirement of a crop. Specifically, we quantify the likely changes in irrigation water demands at a location in the command area, as a response to the projected changes in precipitation and evapotranspiration at that location. Statistical downscaling with a canonical correlation analysis is carried out to develop the future scenarios of meteorological variables (rainfall, relative humidity (RH), wind speed (U₂), radiation, maximum (Tmax) and minimum (Tmin) temperatures) starting with simulations provided by a GCM for a specified emission scenario. The medium resolution Model for Interdisciplinary Research on Climate GCM is used with the A1B scenario, to assess the likely changes in irrigation demands for paddy, sugarcane, permanent garden and semidry crops over the command area of Bhadra reservoir, India. Results from the downscaling model suggest that the monthly rainfall is likely to increase in the reservoir command area. RH, Tmax and Tmin are also projected to increase with small changes in U₂. Consequently, the reference evapotranspiration, modeled by the Penman–Monteith equation, is predicted to increase. The irrigation requirements are assessed on monthly scale at nine selected locations encompassing the Bhadra reservoir command area. The irrigation requirements are projected to increase, in most cases, suggesting that the effect of projected increase in rainfall on the irrigation demands is offset by the effect due to projected increase/change in other meteorological variables (viz., Tmax and Tmin, solar radiation, RH and U₂). The irrigation demand assessment study carried out at a river basin will be useful for future irrigation management systems. Copyright © 2012 John Wiley & Sons, Ltd.     

Possible climate change/variability and human impacts,vulnerability of drought-prone regions,water resources and capacity building for Africa

ABSTRACT

This review article discusses the climate, water resources and historical droughts of Africa, drought indices, vulnerability, impact of global warming and land use for drought-prone regions in West, southern and the Greater Horn of Africa, which have suffered recurrent severe droughts in the past. Recent studies detected warming and drying trends in Africa since the mid 20th century. Based on the Fourth Assessment Report of the Intergovernmental Panel on Climate Change and the Coupled Model Intercomparison Project Phase 5 (CMIP5), both northern and southern Africa are projected to experience drying, such as decreasing precipitation, runoff and soil moisture in the 21st century and could become more vulnerable to the impact of droughts. The daily maximum temperature is projected to increase by up to 8°C (RCP8.5 of CMIP5), precipitation indices such as total wet day precipitation (PRCPTOT) and heavy precipitation days (R10 mm) could decrease, while warm spell duration (WSDI) and consecutive dry days (CDD) could increase. Uncertainties of the above long-term projections, teleconnections to climate anomalies such as ENSO and the Madden-Julian Oscillation, which could also affect the water resources of Africa, and capacity building in terms of physical infrastructure and non-structural solutions are also discussed. Given that traditional climate and hydrological data observed in Africa are generally limited, satellite data should also be exploited to fill the data gap for Africa in the future.

Editor D. Koutsoyiannis; Associate editor N. Ilich     

Comparison of scenario‐neutral approaches for estimation of climate change impacts on flood characteristics

Scenario‐neutral assessments of climate change impact on floods analyse the sensitivity of a catchment to a range of changes in selected meteorological variables such as temperature and precipitation. The key challenges of the approach are the choice of the meteorological variables and statistics thereof and how to generate time series representing altered climatologies of the selected variables. Different methods have been proposed to achieve this, and it remains unclear if and to which extent they result in comparable flood change projections. Here, we compare projections of annual maximum floods (AMFs) derived from three different scenario‐neutral methods for a prealpine study catchment. The methods chosen use different types of meteorological data, namely, observations, regional climate model output, and weather generator data. The different time series account for projected changes in the seasonality of temperature and precipitation, in the occurrence statistics of precipitation, and of daily precipitation extremes. Resulting change in mean AMF peak magnitudes and volumes differs in sign between the methods (range of ?6% to +7% for flood peak magnitudes and ?11% to +14% for flood volumes). Moreover, variability of projected peak magnitudes and flood volumes depends on method with one approach leading to a generally larger spread. The differences between the methods vary depending on whether peak magnitudes or flood volumes are considered and different relationships between peak magnitude and volume change result. These findings can be linked to differing flood regime changes among the three approaches. The study highlights that considering selected aspects of climate change only when performing scenario‐neutral studies may lead to differing representations of flood generating processes by the approaches and thus different quantifications of flood change. As each method comes with its own strengths and weaknesses, it is recommended to combine several scenario‐neutral approaches to obtain more robust results.     

Floodplain catastrophes in the UK Holocene: messages for managing climate change

Floodplains may be transformed when environmental changes or human activity causes alluvial systems to cross channel pattern thresholds. Thresholds between pattern states based on occurrence fields are only available for some pattern distinctions, and these may not encompass the alluvial contexts and range of dynamic factors involved. Pattern changes now known from the UK Holocene are reviewed as a basis for appreciating the potential for future transformations in a changing environment. These involved episodic boulder and gravel spreads in upland environments, and braiding meandering, anastomosing → meandering and active inactive transformations in more lowland contexts. Concern for possible impacts of climatic change need to be grounded in an appreciation of the nature and scale of these past changes. Some potential future changes may be relatively predictable in location (braiding meandering); others are more difficult given both present knowledge and the varying, modified and inheritance‐rich ‘contexts of vulnerability’ that floodplains now represent. Implications for management are discussed. Copyright © 2010 John Wiley & Sons, Ltd.     

Quantifying the impacts of climate change on water resources in northern Tuscany,Italy, using high‐resolution regional projections

This paper investigates the potential impacts of climate change on water resources in northern Tuscany, Italy. A continuous hydrological model for each of the seven river basins within the study area was calibrated using historical data. The models were then driven by downscaled and bias‐corrected climate projections of an ensemble of 13 regional climate models (RCMs), under two different scenarios of representative concentration pathway (RCP4.5 and RCP8.5). The impacts were examined at medium term (2031–2040) and long term (2051–2060) in comparison with a reference period (2003–2012); the changes in rainfall, streamflow, and groundwater recharge were investigated. A high degree of uncertainty characterized the results with a significant intermodel variability, the period being equal. For the sake of brevity, only the results for the Serchio River basin were presented in detail. According to the RCM ensemble mean and the RCP4.5, a moderate decrease in rainfall, with reference to 2003–2012, is expected at medium term (?0.6%) and long term (?2.8%). Due to the warming of the study area, the reduction in the streamflow volume is two times the precipitation decrease (?1.1% and ?6.8% at medium and long term, respectively). The groundwater recharge is mainly affected by the changes in climate with expected percolation volume variations of ?3.3% at 2031–2040 and ?8.1% at 2051–2060. The impacts on the Serchio River basin water resources are less significant under the RCP8.5 scenario. The presence of artificial structures, such as dam‐reservoir systems, can contribute to mitigate the effects of climate change on water resources through the implementation of appropriate regulation strategies.     

Climate models and hydrological parameter uncertainties in climate change impacts on monthly runoff and daily flow duration curve of a Mediterranean catchment

ABSTRACT

Climate models and hydrological parameter uncertainties were quantified and compared while assessing climate change impacts on monthly runoff and daily flow duration curve (FDC) in a Mediterranean catchment. Simulations of the Soil and Water Assessment Tool (SWAT) model using an ensemble of behavioural parameter sets derived from the Generalized Likelihood Uncertainty Estimation (GLUE) method were approximated by feed-forward artificial neural networks (FF-NN). Then, outputs of climate models were used as inputs to the FF-NN models. Subsequently, projected changes in runoff and FDC were calculated and their associated uncertainty was partitioned into climate model and hydrological parameter uncertainties. Runoff and daily discharge of the Chiba catchment were expected to decrease in response to drier and warmer climatic conditions in the 2050s. For both hydrological indicators, uncertainty magnitude increased when moving from dry to wet periods. The decomposition of uncertainty demonstrated that climate model uncertainty dominated hydrological parameter uncertainty in wet periods, whereas in dry periods hydrological parametric uncertainty became more important.

Editor M.C. Acreman; Associate editor S. Kanae     

Exploring impacts of development and climate change on stormwater runoff

Stormwater runoff is a leading cause of non‐point source pollution in urbanizing areas, and runoff effects will be exacerbated by climate's changing patterns of precipitation. To enhance understanding of impacts of development and climate change on stormwater runoff in small watersheds (< 6500 ha), we developed the Stormwater Runoff Modeling System (SWARM), a simple modeling system based on U.S. Department of Agriculture, Natural Resources Conservation Service curve number and unit hydrograph methods. The objective of this paper is to describe the applications possible with SWARM and to demonstrate its usefulness in exploring the impacts of development and climate change on runoff. Results encompass a range of impact scenarios. One development scenario shows that the amount of rainfall converted to runoff is 27% for an undeveloped area and 67% for a highly developed area. A climate scenario shows that the amount of rainfall converted to runoff in a medium developed area is 25% in drought conditions and 76% in wet conditions. User‐friendly templates make SWARM a good tool for scientific research, for resource management and decision making, and for community science education. The modeling system also supports the investigation of social and economic impacts to communities as they adapt to increased development and climate change. Although we calibrated SWARM specifically to the southeast coastal plain, it can be applied to other regions by recalibrating parameters and modifying calculation templates. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.     

Investigating the uncertainty and transferability of parameters in SWAT model under climate change

ABSTRACT

There is an implicit assumption in most work that the parameters calibrated based on observations remain valid for future climatic conditions. However, this might not be true due to parameter instability. This paper investigates the uncertainty and transferability of parameters in a hydrological model under climate change. Parameter transferability is investigated with three parameter sets identified for different climatic conditions, which are: wet, intermediate and dry. A parameter set based on the baseline period (1961–1990) is also investigated for comparison. For uncertainty analysis, a k-simulation set approach is proposed instead of employing the traditional optimization method which uses a single best-fit parameter set. The results show that the parameter set from the wet sub-period performs the best when transferred into wet climate condition, while the parameter set from the baseline period is the most appropriate when transferred into dry climate condition. The largest uncertainty of simulated daily high flows for 2011–2040 is from the parameter set trained in the dry sub-period, while that of simulated daily medium and low flows lies in the parameter set from the intermediate calibration sub-period. For annual changes in the future period, the uncertainty with the parameter set from the intermediate sub-period is the largest, followed by the wet sub-period and dry sub-period. Compared with high and medium flows/runoffs, the uncertainty of low flows/runoffs is much smaller for both simulated daily flows and annual runoffs. For seasonal runoffs, the largest uncertainty is from the intermediate sub-period, while the smallest is from the dry sub-period. Apart from that, the largest uncertainty can be observed for spring runoffs and the lowest one for autumn runoffs. Compared with the traditional optimization method, the k-simulation set approach shows many more advantages, particularly being able to provide uncertainty information to decision support for watershed management under climate change.

EDITOR Z.W. Kundzewicz ASSOCIATE EDITOR not assigned     

The relative impacts of climate change and urbanization on the hydrological response of a Korean urban watershed

We assessed the relative hydrological impacts of climate change and urbanization using an integrated approach that links the statistical downscaling model (SDSM), the Hydrological Simulation Program—Fortran (HSPF) and the impervious cover model (ICM). A case study of the Anyangcheon watershed, a representative urban region in Korea, illustrates how the proposed framework can be used to analyse the impacts of climate change and urbanization on water quantity and quality. The evaluation criteria were measurements of low flow (99, 95, and 90 percentile flow), high flow (10, 5, and 1 percentile value), pollutant concentration (30, 10, and 1 percentile value), and the numbers of days required to satisfy the target water quantity and quality for a sensitive comparison of subtle impacts of variations in these measures. Nine scenarios, including three climate scenarios (present conditions, A1B, and A2) and three land use change scenarios, were analysed using the HSPF model. The impacts of climate change on low flow (34·1–59·8% increase) and high flow (29·1–37·1% increase) were found to be much greater than those on the biochemical oxygen demand (BOD) (3·8–10·0% decrease). On the other hand, the impacts of urbanization on water quality (19·0–44·6% increase) are more significant than those on high (1·0–4·4% increase) and low flow (11·4–25·6% decrease). Furthermore, low flows are more sensitive to urbanization than high flows. The number of days required to satisfy the target water quantity and quality can be a sensitive criterion to compare the subtle impacts of climate and urbanization on human society, especially as they are much more sensitive than low flow and pollutant concentration. Finally, urbanization has a potent impact on BOD while climate change has a high impact on flow rate. Therefore, the impacts of both climate change and urbanization must be included in watershed management and water resources planning for sustainable development. Copyright © 2010 John Wiley & Sons, Ltd.     

Quantifying the impacts of climate change and land use/cover change on runoff in the lower Connecticut River Basin

Climate change and land use and cover change (LUCC) have had great impacts on watershed hydrological processes. Although previous studies have focused on quantitative assessment of the impacts of climate change and human activities on decreasing run‐off change, few studies have examined regions that have significant increasing run‐off due to both climate variability and land cover change. We show that annual run‐off had a significant increasing trend from 1956 to 2014 in the U.S. lower Connecticut River Basin. Abrupt change point years of annual run‐off for four subbasins are detected by nonparametric Mann–Kendall–Sneyers test and reconfirmed by the double mass curve. We then divide the study period into 2 subperiods at the abrupt change point year in the early 1970s for each subbasin. The Choudhury–Yang equation based on Budyko hypothesis was used to calculate precipitation and potential evapotranspiration, and landscape elasticities of run‐off. The results show that the difference in mean annual run‐off between 2 subperiods for each subbasin ranged from 102 to 165.6 mm. Climate variations were the primary drivers of increasing run‐off in this region. Quantitative contributions of precipitation and potential evapotranspiration in all subbasins are 106.5% and ?3.6% on average, respectively. However, LUCC contributed both positively and negatively to run‐off: ?18.6%, ?13.3%, and 10.1% and 9.9% for 4 subbasins. This may be attributed to historical LUCC occurring after the abrupt change point in each subbasin. Our results provide critical insight on the hydrological dynamics of north‐east tidal river systems to communities and policymakers engaged in water resources management in this region.     

Channel and floodplain response to recent abrupt climate change: The tyne basin,Northern England

This paper examines the timing, nature and magnitude of river response in upland, piedmont and lowland reaches of the Tyne basin, northern England, to high-frequency (20–30 year) changes in climate and flood regime since 1700 AD. Over this period fluvial activity has been characterized by alternating phases of river-bed incision and stability coinciding with non-random, decadal-scale fluctuations in flood frequency and hydroclimate that appear to be linked to changes in large-scale upper atmospheric circulation patterns. Episodes of widespread channel bed incision (1760–1799, 1875–1894, 1955–1969) result from a higher frequency of large floods (> 20 year return period) and cool, wet climate under meridional circulation regimes. Phases of more moderate floods (5–20 year return period), corresponding to zonal circulation types (1820–1874, 1920–1954), are characterized by enhanced lateral reworking and sediment transfer in upper reaches of the catchment, and channel narrowing and infilling downstream. Rates of fluvial activity are reduced in intermediate periods (1800–1819, 1895–1919) with no dominant circulation regime associated with lower flood frequency and magnitude. The results of this study provide a valuable guide for forecasting probable drainage basin and channel response to future climate change.     

A new analytical solution for assessing climate change impacts on subsurface temperature

Groundwater temperature is an important water quality parameter that affects species distributions in subsurface and surface environments. To investigate the response of subsurface temperature to atmospheric climate change, an analytical solution is derived for a one‐dimensional, transient conduction–advection equation and verified with numerical methods using the finite element code SUTRA. The solution can be directly applied to forward model the impact of future climate change on subsurface temperature profiles or inversely applied to produce a surface temperature history from measured borehole profiles. The initial conditions are represented using superimposed linear and exponential functions, and the boundary condition is expressed as an exponential function. This solution expands on a classic solution in which the initial and boundary conditions were restricted to linear functions. The exponential functions allow more flexibility in matching climate model projections (boundary conditions) and measured temperature–depth profiles (initial conditions). For example, measured borehole temperature data from the Sendai Plain and Tokyo, Japan, were used to demonstrate the improved accuracy of the exponential function for replicating temperature–depth profiles. Also, the improved accuracy of the exponential boundary condition was demonstrated using air temperature anomaly data from the Intergovernmental Panel on Climate Change. These air temperature anomalies were then used to forward model the effect of surficial thermal perturbations in subsurface environments with significant groundwater flow. The simulation results indicate that recharge can accelerate shallow subsurface warming, whereas upward groundwater discharge can enhance deeper subsurface warming. Additionally, the simulation results demonstrate that future groundwater temperatures obtained from the proposed analytical solution can deviate significantly from those produced with the classic solution. Copyright © 2013 John Wiley & Sons, Ltd.