Hydrological Modelling Framework Research Articles

Modeling the potential for floodwater recharge to offset groundwater depletion: a case study from the Ramganga basin, India

The Ganges basin faces considerable spatial and temporal imbalance between water demand and availability. Lack of water storage infrastructure has led to this mismatch, wherein there are limited options to store flood water during the wet season and limited groundwater and surface water resources during the dry season. In this current study, a semi-coupled hydrological modeling framework is used to test scenarios that can help bridge this imbalance. A hydrological model (SWAT), groundwater model (MODFLOW) and flood inundation model (HEC-RAS) were applied to the Ramganga basin in India (~19,000 km2) to understand the baseline hydrologic regime and to test scenarios with distributed managed aquifer recharge (MAR) interventions, which when applied to at the basin scale to co-address flooding and groundwater depletion has come to be known as Underground Taming of Floods for Irrigation. The scenarios with MAR, which used available basin runoff to recharge groundwater, yielded favorable results in flood reduction and groundwater level improvement throughout the sub-basin. Groundwater levels improved within 5 years of introducing MAR, resulting in a groundwater elevation increase of up to 7 m when compared to baseline conditions. The HEC-RAS model indicated that a 20% reduction in basin outflow converted a 15-year flood peak to an 8-year flood peak, a 5-year peak to 3 years and a 2-year peak to 1 year. In addition, this resulted in a 10% reduction in the inundated area in all return periods tested. Therefore, distributed MAR practices can be effective in reducing the negative impacts from larger return period floods and increasing the groundwater levels.

Hydrological threats to riparian wetlands of international importance – a global quantitative and qualitative analysis

Abstract. Riparian wetlands have been disappearing at an accelerating rate. Their ecological integrity as well as their vital ecosystem services for humankind depend on regular patterns of inundation and drying provided by natural flow regimes. However, river hydrology has been altered worldwide. Dams cause less variable flow regimes and water abstractions decrease the amount of flow so that ecologically important flood pulses are often reduced. Given growing population pressure and projected climate change, immediate action is required. However, the implementation of counteractive measures is often a complex task. This study develops a screening tool for assessing hydrological threats to riparian wetlands on global scales. The approach is exemplified on 93 Ramsar sites, many of which are located in transboundary basins. First, the WaterGAP3 hydrological modeling framework is used to quantitatively compare current and future modified flow regimes to reference flow conditions. In our simulations current water resource management seriously impairs riparian wetland inundation at 29 % of the analyzed sites. A further 8 % experience significantly reduced flood pulses. In the future, eastern Europe, western Asia, as well as central South America could be hotspots of further flow modifications due to climate change. Second, a qualitative analysis of the 93 sites determined potential impact on overbank flows resulting from planned or proposed dam construction projects. They take place in one-third of the upstream areas and are likely to impair especially wetlands located in South America, Asia, and the Balkan Peninsula. Third, based on the existing legal/institutional framework and water resource availability upstream, further qualitative analysis evaluated the capacity to preserve overbank flows given future streamflow changes due to dam construction and climate change. Results indicate hotspots of vulnerability exist, especially in northern Africa and the Persian Gulf.

Evaluation of Quantitative Precipitation Estimations through Hydrological Modeling in IFloodS River Basins

Abstract A multiple-product-driven hydrologic modeling framework (MMF) is utilized for evaluation of quantitative precipitation estimation (QPE) products, motivated by improving the utility of satellite QPE in global flood modeling. This work addresses the challenge of objectively determining the relative value of various QPEs at river basin/subbasin scales. A reference precipitation dataset is created using a long-term water-balance approach with independent data sources. The intercomparison of nine QPEs and corresponding hydrologic simulations indicates that all products with long-term (2002–13) records have similar merits as over the short-term (April–June 2013) Iowa Flood Studies period. The model performance in calculated streamflow varies approximately linearly with precipitation bias, demonstrating that the model successfully translated the level of precipitation quality to streamflow quality with better streamflow simulations from QPEs with less bias. Phase 2 of the North American Land Data Assimilation System (NLDAS-2) has the best streamflow results for the Iowa–Cedar River basin, with daily and monthly Nash–Sutcliffe coefficients and mean annual bias of 0.81, 0.88, and −2.1%, respectively, for the long-term period. The evaluation also indicates that a further adjustment of NLDAS-2 to form the best precipitation estimation should consider spatial–temporal distribution of bias. The satellite-only products have lower performance (peak and timing) than other products, while simple bias adjustment can intermediately improve the quality of simulated streamflow. The TMPA research product (TMPA-RP; research-quality data) can generate results approaching those of the ground-based products with only monthly gauge-based adjustment to the TMPA real-time product (TMPA-RT; near-real-time data). It is further noted that the streamflow bias is strongly correlated to precipitation bias at various time scales, though other factors may play a role as well, especially on the daily time scale.

The FLASH Project: Improving the Tools for Flash Flood Monitoring and Prediction across the United States

Abstract This study introduces the Flooded Locations and Simulated Hydrographs (FLASH) project. FLASH is the first system to generate a suite of hydrometeorological products at flash flood scale in real-time across the conterminous United States, including rainfall average recurrence intervals, ratios of rainfall to flash flood guidance, and distributed hydrologic model–based discharge forecasts. The key aspects of the system are 1) precipitation forcing from the National Severe Storms Laboratory (NSSL)’s Multi-Radar Multi-Sensor (MRMS) system, 2) a computationally efficient distributed hydrologic modeling framework with sufficient representation of physical processes for flood prediction, 3) capability to provide forecasts at all grid points covered by radars without the requirement of model calibration, and 4) an open-access development platform, product display, and verification system for testing new ideas in a real-time demonstration environment and for fostering collaborations. This study assesses the FLASH system’s ability to accurately simulate unit peak discharges over a 7-yr period in 1,643 unregulated gauged basins. The evaluation indicates that FLASH’s unit peak discharges had a linear and rank correlation of 0.64 and 0.79, respectively, and that the timing of the peak discharges has errors less than 2 h. The critical success index with FLASH was 0.38 for flood events that exceeded action stage. FLASH performance is demonstrated and evaluated for case studies, including the 2013 deadly flash flood case in Oklahoma City, Oklahoma, and the 2015 event in Houston, Texas—both of which occurred on Memorial Day weekends.

Development of a dual permeability model within a hydrological catchment modeling framework: 1D application

Preferential flow contributes significantly to pesticide fast transfer from surface to groundwater. Modeling this process at several scales is an important challenge for improving the representation of this process which is often neglected. In this study, we developed a dual permeability approach in a hydrological modeling framework, CMF, which is a collaborative environment for developing spatially-integrated models of water fluxes. In the development we propose here, infiltration in macropores which are connected to the surface is activated when the first matrix layer reaches saturation. A transfer function is used to represent water fluxes from macropores to matrix. This approach is tested in 1D by comparison with the dual permeability approach included in Hydrus1D, on 4 typical soil-types (sandy-loam, silty-loam, clay-loam and sandy-clay-loam). The results showed an underestimation of the flux infiltrated in the matrix surface and important infiltration in macropores with the new model, for most of soil-types, comparing to Hydrus1D. Similarities are observed for fluxes transferred from macropores to matrix. Solute transport is then coupled to CMF-DP model considering a convection transport and a linear adsorption to represent pesticides behavior in macroporous soils. The approach we developed is similar to Hydrus though having the advantage to need less input parameters, especially for the exchange between the two porous media. In the future, it could be applied for predicting pesticides transfer in macroporous soils at different scales for operational applications.

Quantifying the contribution of glacier meltwater in the expansion of the largest lake in Tibet

AbstractLake Siling Co is currently the largest endorheic lake in Tibet, and the lake surface area has expanded by about 40% since the 1970s, with a remarkable acceleration after 1999. In this study, a hydrologic modeling framework was established by linking the Variable Infiltration Capacity (VIC) land surface hydrologic model with the degree‐day glacier‐melt model over the Lake Siling Co basin, with an aim to quantify the contribution of each runoff component to changes in the lake storage. We found that glacier melt contributed to less than 10% of the total water input to the lake during 1979–2013, while precipitation‐induced runoff in nonglacierized area was responsible for about 67–75%. The mean annual water input to the lake increased by 2.15 × 109 m3 yr−1 in 2000–2013 relative to that in 1979–1999. The amount of precipitation over the lake surface, precipitation‐induced runoff, and glacier‐melt runoff accounted for 13%, 82%, and 5% of this total increase, respectively, suggesting that the substantial expansion of Siling Co in the 2000s was mostly due to the increase in precipitation‐induced runoff. When modeling lake level changes during 1979–2013, we found that the water level rose by 14.1 m when glacier melt was included and by only 10.5 m, a reduction of about one fourth, when glacier melt was removed. It is concluded that glacier melt played an important role in controlling the water level of Siling Co, although it only contributed less than 10% of water input to the lake during 1979–2013.

Reliability of lumped hydrological modeling in a semi-arid mountainous catchment facing water-use changes

Abstract. This paper explores the reliability of a hydrological modeling framework in a mesoscale (1515 km2) catchment of the dry Andes (30° S) where irrigation water use and snow sublimation represent a significant part of the annual water balance. To this end, a 20-year simulation period encompassing a wide range of climate and water-use conditions was selected to evaluate three types of integrated models referred to as A, B and C. These models share the same runoff generation and routing module but differ in their approach to snowmelt modeling and irrigation water use. Model A relies on a simple degree-day approach to estimate snowmelt rates and assumes that irrigation impacts can be neglected at the catchment scale. Model B ignores irrigation impacts just as Model A but uses an enhanced degree-day approach to account for the effects of net radiation and sublimation on melt rates. Model C relies on the same snowmelt routine as Model B but incorporates irrigation impacts on natural streamflow using a conceptual irrigation module. Overall, the reliability of probabilistic streamflow predictions was greatly improved with Model C, resulting in narrow uncertainty bands and reduced structural errors, notably during dry years. This model-based analysis also stressed the importance of considering sublimation in empirical snowmelt models used in the subtropics, and provided evidence that water abstractions from the unregulated river are impacting on the hydrological response of the system. This work also highlighted areas requiring additional research, including the need for a better conceptualization of runoff generation processes in the dry Andes.

Suitability of Water Harvesting in the Upper Blue Nile Basin, Ethiopia: A First Step towards a Mesoscale Hydrological Modeling Framework

Extreme rainfall variability has been one of the major factors to famine and environmental degradation in Ethiopia. The potential for water harvesting in the Upper Blue Nile Basin was assessed using two GIS-based Multicriteria Evaluation methods: (1) a Boolean approach to locate suitable areas for in situ and ex situ systems and (2) a weighted overlay analysis to classify suitable areas into different water harvesting suitability levels. The sensitivity of the results was analyzed to the influence given to different constraining factors. A large part of the basin was suitable for water harvesting: the Boolean analysis showed that 36% of the basin was suitable for in situ and ex situ systems, while the weighted overlay analysis showed that 6–24% of the basin was highly suitable. Rainfall has the highest influence on suitability for water harvesting. Implementing water harvesting in nonagricultural land use types may further increase the benefit. Assessing water harvesting suitability at the larger catchment scale lays the foundation for modeling of water harvesting at mesoscale, which enables analysis of the potential and implications of upscaling of water harvesting practices for building resilience against climatic shocks. A complete water harvesting suitability study requires socioeconomic analysis and stakeholder consultation.

Global Topographic Slope Enforcement to Ensure Connectivity and Drainage in an Urban Terrain

AbstractSources of high-resolution topographic data, such as LiDAR, characterize urban terrains in great detail and can provide a resource for distributed hydrologic modeling. Incorporating these data in a distributed hydrologic modeling framework is complicated by the numerous real and artificial pits, barriers, and surface depressions contained in the urban landscape. These features create difficulties with simulating surface drainage that must be resolved to ensure model stability and convergence. This study presents a methodology to calculate distributed slope fields from LiDAR-based digital elevation models (DEM) that addresses this problem and preserves topographic details. This global slope enforcement approach ensures complete domain drainage, and the effects are demonstrated by performing a rainfall-recession test on an impervious domain using a distributed hydrologic model (ParFlow) of an urban watershed in Baltimore. This study shows that the fraction of rainfall input retained as surface stora...

Assessment of the impact of spatio-temporal attributes of wetlands on stream flows using a hydrological modelling framework: a theoretical case study of a watershed under temperate climatic conditions

Wetlands play a significant role on the hydrological cycle, reducing flood peaks through water storage functions and sustaining low flows through slow water release ability. However, their impacts on water resources availability and flood control are mainly driven by wetland type (e.g., isolated wetland –IW- and riparian wetland –RW-) and location within a watershed. Consequently, assessing the qualitative and quantitative impact of wetlands on hydrological regimes has become a relevant issue for scientists as well as stakeholders and decision-makers. In this study, the distributed hydrological model, HYDROTEL, was used to investigate the role and impact of the geographic distribution of isolated and riparian wetlands on stream flows of the Becancour River watershed of the St Lawrence Lowlands, Quebec, Canada. The model was set up and calibrated using available datasets (i.e., DEM, soil, wetland distribution, climate, land cover, and hydrometeorological data for the 1969-2010 period). Different Wetland Theoretical Location Tests (WTLT) were simulated. Results were used to determine whether stream flow parameters, related to peak flows and low flows, were related to: (i) geographic location of wetlands, (ii) typology of wetlands, and (iii) seasonality. The contribution of a particular wetland was assessed using intrinsic characteristics (e.g., surface area, typology) and extrinsic factors (e.g., location in the watershed landscape and seasonality). Through these investigations, the results suggest, to some extent, that both IWs and RWs impact landscape hydrology. The more IWs are located in the upper part of the watershed, the greater their effect on both on high flow damping and low flow support seems to be. The more RWs are connected to a main stream, the greater their effect is. Our modelling results indicate that local landscape conditions may influence the wetland effect; promoting or limiting their efficiency, and thus their impacts on stream flows depend on a combined effect of wetland and landscape attributes.

Characterizing the hydraulic interactions of hurricane storm surge and rainfall–runoff for the Houston–Galveston region

Planning of traditional coastal flood risk management strategies are largely predicated on storm surge protection against extreme hurricanes, i.e. storm surge. However, (1) hurricane storm surge and (2) hurricane rainfall–runoff are not mutually exclusive flood hazards. Little research has emphasized the need for quantifying and characterizing the joint hydraulic processes between hurricane storm surge and rainfall–runoff during real events for enhancing effective flood risk mitigation. In this regard, an improved hydrological and hydrodynamic modeling framework has been developed for the Houston Ship Channel (HSC) and Galveston Bay to serve as a quantitative testbed for evaluating coupled hurricane storm surge and rainfall–runoff. Modularity within the modeling framework allows for landfall shifting of historical hurricane tracks, wind fields, and corresponding rainfall patterns to serve as numerical model inputs, as well as providing an expanded dataset of storm events. Distributed hydrologic and unsteady hydraulic analyses of upstream rainfall–runoff and storm surge are conducted for hurricanes Katrina (2005), Ike (2008), and Isaac (2012) under three synthetically shifted landfall locations near the HSC and Galveston Bay regions. For the modeled scenarios, results show that peak flows from storm surge easily dominate those of rainfall–runoff, but that rainfall–runoff can constitute more than half of the total flood volume draining towards the HSC. Most modeled scenarios reveal less than 24h of separation between peak surge and peak rainfall–runoff. In the same way that storm surge is sensitive to hurricane landfall location and angle of approach, so are spatial rainfall distributions and associated inland runoff processes, due to wide topological variations in coastal watershed boundaries. Analysis of coastal flood mitigation is extended with the dynamic modeling of a proposed storm surge barrier system at the HSC, with its performance quantified under the given hurricanes. The surge barrier system is demonstrated to be hydraulically feasible for all scenarios, with maximum water surface elevation reductions ranging between 0.63m and 3.28m. However, accurate storm surge and riverine flood forecasting methods will be critical for achieving optimal gate and barrier operations.

Integrated simulation of snow and glacier melt in water and energy balance‐based, distributed hydrological modeling framework at Hunza River Basin of Pakistan Karakoram region

AbstractEnergy budget‐based distributed modeling of snow and glacier melt runoff is essential in a hydrologic model to accurately describe hydrologic processes in cold regions and high‐altitude catchments. We developed herein an integrated modeling system with an energy budget‐based multilayer scheme for clean glaciers, a single‐layer scheme for debris‐covered glaciers, and multilayer scheme for seasonal snow over glacier, soil, and forest within a distributed biosphere hydrological modeling framework. Model capability is demonstrated for Hunza River Basin (13,733 km2) in the Karakoram region of Pakistan on a 500 m grid for 3 hydrologic years (2002–2004). Discharge simulation results show good agreement with observations (Nash‐Sutcliffe efficiency = 0.93). Flow composition analysis reveals that the runoff regime is strongly controlled by the snow and glacier melt runoff (50% snowmelt and 33% glacier melt). Pixel‐by‐pixel evaluation of the simulated spatial distribution of snow‐covered area against Moderate Resolution Imaging Spectroradiometer‐derived 8 day maximum snow cover extent data indicates that the areal extent of snow cover is reproduced well, with average accuracy 84% and average absolute bias 7%. The 3 year mean value of net mass balance (NMB) was estimated at +0.04 myr−1. It is interesting that individual glaciers show similar characteristics of NMB over 3 years, suggesting that both topography and glacier hypsometry play key roles in glacier mass balance. This study provides a basis for potential application of such an integrated model to the entire Hindu‐Kush‐Karakoram‐Himalaya region toward simulating snow and glacier hydrologic processes within a water and energy balance‐based, distributed hydrological modeling framework.

Sensitivity of potential evaporation estimates to 100 years of climate variability

Abstract. Hydrological modeling frameworks require an accurate representation of evaporation fluxes for appropriate quantification of, e.g., the water balance, soil moisture budget, recharge and groundwater processes. Many frameworks have used the concept of potential evaporation, often estimated for different vegetation classes by multiplying the evaporation from a reference surface ("reference evaporation") by crop-specific scaling factors ("crop factors"). Though this two-step potential evaporation approach undoubtedly has practical advantages, the empirical nature of both reference evaporation methods and crop factors limits its usability in extrapolations under non-stationary climatic conditions. In this paper, rather than simply warning about the dangers of extrapolation, we quantify the sensitivity of potential evaporation estimates for different vegetation classes using the two-step approach when calibrated using a non-stationary climate. We used the past century's time series of observed climate, containing non-stationary signals of multi-decadal atmospheric oscillations, global warming, and global dimming/brightening, to evaluate the sensitivity of potential evaporation estimates to the choice and length of the calibration period. We show that using empirical coefficients outside their calibration range may lead to systematic differences between process-based and empirical reference evaporation methods, and systematic errors in estimated potential evaporation components. Quantification of errors provides a possibility to correct potential evaporation calculations and to rate them for their suitability to model climate conditions that differ significantly from the historical record, so-called no-analog climate conditions.

Catchment response to bark beetle outbreak and dust-on-snow in the Colorado Rocky Mountains

Summary Since 2002, the headwaters of the Colorado River and nearby basins have experienced extensive changes in land cover at sub-annual timescales. Widespread tree mortality from bark beetle infestation has taken place across a range of forest types, elevation, and latitude. Extent and severity of forest structure alteration have been observed through a combination of aerial survey, satellite remote-sensing, and in situ measurements. Additional perturbations have resulted from deposition of dust from regional dry-land sources on mountain snowpacks that strongly alter the snow surface albedo, driving earlier and faster snowmelt runoff. One challenge facing past studies of these forms of disturbance is the relatively small magnitude of the disturbance signals within the larger climatic signal. The combined impacts of forest disturbance and dust-on-snow are explored within a hydrologic modeling framework. We drive the Distributed Hydrology Soil and Vegetation Model (DHSVM) with observed meteorological data, time-varying maps of leaf area index and forest properties to emulate bark beetle impacts, and parameterizations of snow albedo based on observations of dust forcing. Results from beetle-killed canopy alteration suggest slightly greater snow accumulation as a result of less interception and reduced canopy sublimation and evapotranspiration, contributing to overall increases in annual water yield between 8% and 13%. However, understory regeneration roughly halves the changes in water yield. A purely observation-based estimate of runoff coefficient change with cumulative forest mortality shows comparable sensitivities to simulated results; however, positive water yield changes are not statistically significant ( p ⩽ 0.05). The primary hydrologic impact of dust-on-snow forcing is an increased rate of snowmelt associated with more extreme dust deposition, producing earlier peak streamflow rates on the order of 1–3 weeks. Simulations of combined bark beetle and dust-on-snow produced little compounding effects, due to the relatively exclusive nature of their impacts. Potential changes in water yield and peak streamflow timing have important implications for regional water management decisions.

A modelling framework to project future climate change impacts on streamflow variability and extremes in the West River, China

Abstract. In this study, a hydrological modelling framework was introduced to assess the climate change impacts on future river flow in the West River basin, China, especially on streamflow variability and extremes. The modelling framework includes a delta-change method with the quantile-mapping technique to construct future climate forcings on the basis of observed meteorological data and the downscaled climate model outputs. This method is able to retain the signals of extreme weather events, as projected by climate models, in the constructed future forcing scenarios. Fed with the historical and future forcing data, a large-scale hydrologic model (the Variable Infiltration Capacity model, VIC) was executed for streamflow simulations and projections at daily time scales. A bootstrapping resample approach was used as an indirect alternative to test the equality of means, standard deviations and the coefficients of variation for the baseline and future streamflow time series, and to assess the future changes in flood return levels. The West River basin case study confirms that the introduced modelling framework is an efficient effective tool to quantify streamflow variability and extremes in response to future climate change.

A tightly coupled GIS and distributed hydrologic modeling framework

Distributed, physics-based hydrologic models require spatially explicit specification of parameters related to climate, geology, land-cover, soil, and topography. Extracting these parameters from national geodatabases requires intensive data processing. Furthermore, mapping these parameters to model mesh elements necessitates development of data access tools that can handle both spatial and temporal datasets. This paper presents an open-source, platform independent, tightly coupled GIS and distributed hydrologic modeling framework, PIHMgis (www.pihm.psu.edu), to improve model-data integration. Tight coupling is achieved through the development of an integrated user interface with an underlying shared geodata model, which improves data flow between the PIHMgis data processing components. The capability and effectiveness of the PIHMgis framework in providing functionalities for watershed delineation, domain decomposition, parameter assignment, simulation, visualization and analyses, is demonstrated through prototyping of a model simulation. The framework and the approach are applicable for watersheds of varied sizes, and offer a template for future GIS-Model integration efforts.

From Catchment to National Scale Rainfall-Runoff Modelling: Demonstration of a Hydrological Modelling Framework

The increasing availability of digital databases (e.g., of climatology, topography, soils and land use) has enabled research into the generalisation of hydrological model parameter values from physical properties and the development of grid-based models. A hydrological modelling framework (HMF) is being developed to exploit this generalisation and provide a flexible gridded infrastructure, operational over regional, national or larger scales at a range of spatial and temporal resolutions. The capability of the framework is demonstrated through adaptation of an existing semi-distributed catchment-based rainfall-runoff model, CLASSIC, for which a generalised methodology exists to determine parameter values. The main change required was to ensure consistency of parameter values between the runoff procedure in CLASSIC and flow routing in the HMF. Assessment is by comparison of modelled and observed flow at grid points in Britain corresponding to gauging stations, both for catchments previously modelled and for new locations, for a range of catchment areas and physical properties and for four spatial resolutions (10, 5, 2.5 and 1 km). Good model performance is achieved for 90% of catchments tested, with a 5 km resolution proving adequate for catchments larger than 500 km2. Applications are outlined for which the framework could be used to test alternative modelling approaches or undertake consistent studies across the range of resolutions.

Modeling hydrologic and ecologic responses using a new eco‐hydrological model for identification of droughts

AbstractDrought severely damages water and agricultural resources, and both hydrological and ecological responses are important for its understanding. First, precipitation deficit induces soil moisture deficiency and high plant water stress causing agricultural droughts. Second, hydrological drought characterized by deficit of river discharge and groundwater follows agricultural drought. However, contributions of vegetation dynamics to these processes at basin scale have not been quantified. To address this issue, we develop an eco‐hydrological model that can calculate river discharge, groundwater, energy flux, and vegetation dynamics as diagnostic variables at basin scale within a distributed hydrological modeling framework. The model is applied to drought analysis in the Medjerda River basin. From model inputs and outputs, we calculate drought indices for different drought types. The model shows reliable accuracy in reproducing observed river discharge in long‐term (19 year) simulation. Moreover, the drought index calculated from the model‐estimated annual peak of leaf area index correlates well (correlation coefficient r = 0.89) with the drought index from nationwide annual crop production, which demonstrates that the modeled leaf area index is capable of representing agricultural droughts related to historical food shortages. We show that vegetation dynamics have a more rapid response to meteorological droughts than river discharge and groundwater dynamics in the Medjerda basin because vegetation dynamics are sensitive to soil moisture in surface layers, whereas soil moisture in deeper layers strongly contributes to streamflow and groundwater level. Our modeling framework can contribute to analyze drought progress, although analyses for other climate conditions are needed.

Cost-effective targeting of riparian buffers to achieve water quality and wildlife habitat benefits

ABSTRACTThis study develops an integrated economic, hydrologic, and ecological modelling framework to examine cost-effective targeting of riparian buffers to achieve water quality and wildlife habitat benefits. The framework is empirically applied to the Canagagigue Creek watershed in Ontario, Canada to compare the economic costs for establishing riparian buffers under three alternative environmental and ecological constraints: sediment abatement only, habitat improvement only, and riparian buffer acreage only. The results show that riparian buffers targeted for achieving sediment abatement goal are not effective in improving habitat quality. Similarly, riparian buffers identified through habitat improvement goal achieve less sediment abatement as compared to those targeted in the sediment abatement scenario. The trade-offs suggest that agricultural stewardship programmes with joint water quality and habitat improvement goals may need to allocate funds independently for targeting two pools of riparian buffers: for improving water quality only or for improving habitat only.

Global streamflow and thermal habitats of freshwater fishes under climate change

Climate change will affect future flow and thermal regimes of rivers. This will directly affect freshwater habitats and ecosystem health. In particular fish species, which are strongly adapted to a certain level of flow variability will be sensitive to future changes in flow regime. In addition, all freshwater fish species are exotherms, and increasing water temperatures will therefore directly affect fishes’ biochemical reaction rates and physiology. To assess climate change impacts on large-scale freshwater fish habitats we used a physically-based hydrological and water temperature modelling framework forced with an ensemble of climate model output. Future projections on global river flow and water temperature were used in combination with current spatial distributions of several fish species and their maximum thermal tolerances to explore impacts on fish habitats in different regions around the world. Results indicate that climate change will affect seasonal flow amplitudes, magnitude and timing of high and low flow events for large fractions of the global land surface area. Also, significant increases in both the frequency and magnitude of exceeding maximum temperature tolerances for selected fish species are found. Although the adaptive capacity of fish species to changing hydrologic regimes and rising water temperatures could be variable, our global results show that fish habitats are likely to change in the near future, and this is expected to affect species distributions.