Catchment-scale Hydrological Models Research Articles

Multi-model evaluation of catchment- and global-scale hydrological model simulations of drought characteristics across eight large river catchments

Although global- and catchment-scale hydrological models are often shown to accurately simulate long-term runoff time-series, far less is known about their suitability for capturing hydrological extremes, such as droughts. Here we evaluated simulations of hydrological droughts from nine catchment scale hydrological models (CHMs) and eight global scale hydrological models (GHMs) for eight large catchments: Upper Amazon, Lena, Upper Mississippi, Upper Niger, Rhine, Tagus, Upper Yangtze and Upper Yellow. The simulations were conducted within the framework of phase 2a of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a). We evaluated the ability of the CHMs, GHMs and their respective ensemble means (Ens-CHM and Ens-GHM) to simulate observed hydrological droughts of at least one month duration, over 31 years (1971–2001). Hydrological drought events were identified from runoff-deficits and the Standardised Runoff Index (SRI). In all catchments, the CHMs performed relatively better than the GHMs, for simulating monthly runoff-deficits. The number of drought events identified under different drought categories (i.e. SRI values of -1 to -1.49, -1.5 to -1.99, and ≤-2) varied significantly between models. All the models, as well as the two ensemble means, have limited abilities to accurately simulate drought events in all eight catchments, in terms of their occurrence and magnitude. Overall, there are opportunities to improve both CHMs and GHMs for better characterisation of hydrological droughts.

Climatic and anthropogenic drivers of a drying Himalayan river

Abstract. Streamflow regimes are rapidly changing in many regions of the world. Attribution of these changes to specific hydrological processes and their underlying climatic and anthropogenic drivers is essential to formulate an effective water policy. Traditional approaches to hydrologic attribution rely on the ability to infer hydrological processes through the development of catchment-scale hydrological models. However, such approaches are challenging to implement in practice due to limitations in using models to accurately associate changes in observed outcomes with corresponding drivers. Here we present an alternative approach that leverages the method of multiple hypotheses to attribute changes in streamflow in the Upper Jhelum watershed, an important tributary headwater region of the Indus basin, where a dramatic decline in streamflow since 2000 has yet to be adequately attributed to its corresponding drivers. We generate and empirically evaluate a series of alternative and complementary hypotheses concerning distinct components of the water balance. This process allows a holistic understanding of watershed-scale processes to be developed, even though the catchment-scale water balance remains open. Using remote sensing and secondary data, we explore changes in climate, surface water, and groundwater. The evidence reveals that climate, rather than land use, had a considerably stronger influence on reductions in streamflow, both through reduced precipitation and increased evapotranspiration. Baseflow analyses suggest different mechanisms affecting streamflow decline in upstream and downstream regions, respectively. These findings offer promising avenues for future research in the Upper Jhelum watershed, and an alternative approach to hydrological attribution in data-scarce regions.

SuperflexPy 1.3.0: an open-source Python framework for building, testing, and improving conceptual hydrological models

Abstract. Catchment-scale hydrological models are widely used to represent and improve our understanding of hydrological processes and to support operational water resource management. Conceptual models, which approximate catchment dynamics using relatively simple storage and routing elements, offer an attractive compromise in terms of predictive accuracy, computational demands, and amenability to interpretation. This paper introduces SuperflexPy, an open-source Python framework implementing the SUPERFLEX principles (Fenicia et al., 2011) for building conceptual hydrological models from generic components, with a high degree of control over all aspects of model specification. SuperflexPy can be used to build models of a wide range of spatial complexity, ranging from simple lumped models (e.g., a reservoir) to spatially distributed configurations (e.g., nested sub-catchments), with the ability to customize all individual model components. SuperflexPy is a Python package, enabling modelers to exploit the full potential of the framework without the need for separate software installations and making it easier to use and interface with existing Python code for model deployment. This paper presents the general architecture of SuperflexPy, discusses the software design and implementation choices, and illustrates its usage to build conceptual models of varying degrees of complexity. The illustration includes the usage of existing SuperflexPy model elements, as well as their extension to implement new functionality. Comprehensive documentation is available online and provided as a Supplement to this paper. SuperflexPy is available as open-source code and can be used by the hydrological community to investigate improved process representations for model comparison and for operational work.

Reduction of vegetation-accessible water storage capacity after deforestation affects catchment travel time distributions and increases young water fractions in a headwater catchment

Abstract. Deforestation can considerably affect transpiration dynamics and magnitudes at the catchment scale and thereby alter the partitioning between drainage and evaporative water fluxes released from terrestrial hydrological systems. However, it has so far remained problematic to directly link reductions in transpiration to changes in the physical properties of the system and to quantify these changes in system properties at the catchment scale. As a consequence, it is difficult to quantify the effect of deforestation on parameters of catchment-scale hydrological models. This in turn leads to substantial uncertainties in predictions of the hydrological response after deforestation but also to a poor understanding of how deforestation affects principal descriptors of catchment-scale transport, such as travel time distributions and young water fractions. The objectives of this study in the Wüstebach experimental catchment are therefore to provide a mechanistic explanation of why changes in the partitioning of water fluxes can be observed after deforestation and how this further affects the storage and release dynamics of water. More specifically, we test the hypotheses that (1) post-deforestation changes in water storage dynamics and partitioning of water fluxes are largely a direct consequence of a reduction of the catchment-scale effective vegetation-accessible water storage capacity in the unsaturated root zone (SU, max) after deforestation and that (2) the deforestation-induced reduction of SU, max affects the shape of travel time distributions and results in shifts towards higher fractions of young water in the stream. Simultaneously modelling streamflow and stable water isotope dynamics using meaningfully adjusted model parameters both for the pre- and post-deforestation periods, respectively, a hydrological model with an integrated tracer routine based on the concept of storage-age selection functions is used to track fluxes through the system and to estimate the effects of deforestation on catchment travel time distributions and young water fractions Fyw. It was found that deforestation led to a significant increase in streamflow accompanied by corresponding reductions of evaporative fluxes. This is reflected by an increase in the runoff ratio from CR=0.55 to 0.68 in the post-deforestation period despite similar climatic conditions. This reduction of evaporative fluxes could be linked to a reduction of the catchment-scale water storage volume in the unsaturated soil (SU, max) that is within the reach of active roots and thus accessible for vegetation transpiration from ∼258 mm in the pre-deforestation period to ∼101 mm in the post-deforestation period. The hydrological model, reflecting the changes in the parameter SU, max, indicated that in the post-deforestation period stream water was characterized by slightly yet statistically not significantly higher mean fractions of young water (Fyw∼0.13) than in the pre-deforestation period (Fyw∼0.12). In spite of these limited effects on the overall Fyw, changes were found for wet periods, during which post-deforestation fractions of young water increased to values Fyw∼0.37 for individual storms. Deforestation also caused a significantly increased sensitivity of young water fractions to discharge under wet conditions from dFyw/dQ=0.25 to 0.36. Overall, this study provides quantitative evidence that deforestation resulted in changes in vegetation-accessible storage volumes SU, max and that these changes are not only responsible for changes in the partitioning between drainage and evaporation and thus the fundamental hydrological response characteristics of the Wüstebach catchment, but also for changes in catchment-scale tracer circulation dynamics. In particular for wet conditions, deforestation caused higher proportions of younger water to reach the stream, implying faster routing of stable isotopes and plausibly also solutes through the sub-surface.

A 3D hydrogeochemistry model of nitrate transport and fate in a glacial sediment catchment: A first step toward a numerical model

Diffuse pollution of nitrate from agricultural fields is a critical environmental problem around the world. Sources and sinks of nitrate are heterogeneously distributed over various spatial scales, and the connectivity and transport pathways between them also change at different temporal scales. Therefore, understanding the impact of these variabilities in nitrate transport to the aquatic environment is fundamental for a correct numerical modelling of nitrate transport within a catchment. This study, hence, investigated controls on the spatiotemporal variability of nitrate in a glacial landscape and upscaled it to catchment scale by synthesizing geological, hydrogeochemical, and geophysical information. We found that different parts of the sedimentary succession define the locations of nitrate sinks in this catchment. Denitrification mainly may occur mainly around small patches of postglacial sediments on the outwash plain, which is the youngest formation covering the top layer of the catchment. In contrast, in older geological elements, which constitute the hill and the layers below the outwash plain, oxic, nitrate-containing groundwater was found, probably because of depletion of reduced compounds over the long exposure time. We also found that the boundary between these two formations may govern the seasonal shift of this oxic groundwater's connectivity to the stream consequently nitrate export from the catchment. This conceptual understanding of nitrate transport and sinks then was transformed into a 3D hydrogeochemistry model based on a high-resolution resistivity model of the catchment. We propose that such a basic understanding of how a catchment hydrogeochemically operates should be the first step toward setting up a catchment scale hydrological model with reactive N transport. • NO 3 -behavior was studied using geophysical, hydrogeochemical and geological data. • The geological structure may determine the denitrification zones in the study site. • Hydrological connectivity between groundwater and stream may control nitrate load. • Detailed structural data is essential to upscale point data to catchment level.

Simulating water and heat transport with freezing and cryosuction in unsaturated soil: Comparing an empirical, semi-empirical and physically-based approach

Freezing of unsaturated soil is an important process that influences runoff and infiltration in cold-climate regions. We used a simple numerical model to simulate water and heat transport with phase change in unsaturated soil via three different approaches: empirical, semi-empirical and physically based. We compared the performance and parameterization of each approach through testing on three experimental datasets. All approaches reproduced the observed unsaturated freezing process satisfactorily. The empirical cryosuction equation used in this study managed to capture observed cryosuction with a fixed empirical parameter value. The semi-empirical version therefore does not require calibration of a specific frozen soil related parameter. In view of simplicity, small computational demand and accurate performance, all three approaches are suitable for implementation in land-use schemes, catchment scale hydrological models, or multi-dimensional thermo-hydrological models.

Calibration of a modelling approach for sediment yield in a wattle plantation, KwaZulu-Natal, South Africa

Hydrological modelling is an appropriate approach to investigate the effect of interactions of climate, land-use and soil on the water-use of natural or managed ecosystems, in particular where spatial heterogeneity exists. The Soil and Water Assessment Tool (SWAT) model has evolved into one of the most widely used catchment-scale hydrological models, which has been extensively used to better understand hydrological processes. In this paper, the SWAT model was adopted to simulate a wattle plantation in KwaZulu-Natal, South Africa. User-defined vegetation growth, soil and management input parameters were constructed for the study area based on site measurements. These parameters were subsequently modified using the Sequential Uncertainty Fitting (SUFI-2) analysis routine to calibrate the model. The calibrated model captured seasonal trends in the observed sediment and streamflow data. The compilation of spatially explicit sediment output provides a useful approach to manage catchments by identifying high erosion-risk areas. The SWAT model, using site-specific input parameters, provides a platform for subsequent hydrological and sediment modelling in South Africa.

Modeling the future impacts of climate change on water availability in the Karnali River Basin of Nepal Himalaya

It's unequivocal that the global climate is changing, including the rise in atmospheric temperature and variability in amount and pattern of precipitation, and the rate of temperature change in the Himalayan region is higher than the global average. Since precipitation and temperature are the major driving factors of water resources in the Himalayas both upstream and downstream regions, it is important to understand theimpacts of climate change in water resource availability in the future. In this study, we analyzed the historical hydro-climate data and developed a suitable ensemble of the Coordinated Regional Downscaling Experiment (CORDEX) climate models for the Karnali River Basin (KRB) in western Nepal and assessed the future water availability in different climate scenarios using a semi-distributed catchment scale hydrological model the Soil and Water Assessment Tool (SWAT). The climate data analysis shows that the atmospheric temperature is rising throughout the basin but there is high spatial variability in precipitation trend. The historical river discharge data analysis do not show any significant trend, however, there is some inter-annual variability. Future projection shows that the annual precipitation amount will increase compared to the baseline so does the river discharge. However, this increase is not uniform for all seasons. The post-monsoon season having the lowest observed precipitation will get lesser amount of precipitation in the future and the river discharge also follows the same trend. These anomalies play a crucial role in determining the future water availability for agriculture, hydropower, ecosystem functioning and its services availability to the people living in the KRB as well as in the downstream region.

Contributions of catchment and in-stream processes to suspended sediment transport in a dominantly groundwater-fed catchment

Abstract. Suspended sediments impact stream water quality by increasing the turbidity and acting as a vector for strongly sorbing pollutants. Understanding their sources is of great importance to developing appropriate river management strategies. In this study, we present an integrated sediment transport model composed of a catchment-scale hydrological model to predict river discharge, a river-hydraulics model to obtain shear stresses in the channel, a sediment-generating model, and a river sediment-transport model. We use this framework to investigate the sediment contributions from catchment and in-stream processes in the Ammer catchment close to Tübingen in southwestern Germany. The model is calibrated to stream flow and suspended-sediment concentrations. We use the monthly mean suspended-sediment load to analyze seasonal variations of different processes. The contributions of catchment and in-stream processes to the total loads are demonstrated by model simulations under different flow conditions. The evaluation of shear stresses by the river-hydraulics model allows the identification of hotspots and hot moments of bed erosion for the main stem of the Ammer River. The results suggest that the contributions of suspended-sediment loads from urban areas and in-stream processes are higher in the summer months, while deposition has small variations with a slight increase in summer months. The sediment input from agricultural land and urban areas as well as bed and bank erosion increase with an increase in flow rates. Bed and bank erosion are negligible when flow is smaller than the corresponding thresholds of 1.5 and 2.5 times the mean discharge, respectively. The bed-erosion rate is higher during the summer months and varies along the main stem. Over the simulated time period, net sediment trapping is observed in the Ammer River. The present work is the basis to study particle-facilitated transport of pollutants in the system, helping to understand the fate and transport of sediments and sediment-bound pollutants.

Hydrological modelling as a tool for interdisciplinary workshops on future drought

Transformative interdisciplinary methods and tools are required to address crucial water-related challenges facing societies in the current era of the Anthropocene. In a community-based study in the Limpopo basin of South Africa, physical and social science methods were brought together to run interdisciplinary workshops aimed at enhancing preparedness for possible future drought. To generate storylines for the workshops, relevant scenarios were modelled using a catchment-scale hydrological model, SHETRAN. Set up using freely available data, local knowledge, and narrative-based group interviews on past experiences of drought, the model acted as a locally-relevant tool for prompting discussions about potential future drought impacts, responses and preparedness, and to stimulate the production of community future narratives. In this paper, we discuss the elements involved in the modelling process: the building of the model through an interdisciplinary approach; setting up the model with limited data; and the translation of the model results into storylines for the workshops. We found that by using this methodology scientific grounding was given to the workshop storylines, and that the local context of the model and the engaging approach of creating narratives encouraged participant involvement in discussions about the future. The method of generating these future stories was an important process for the participants in developing their thinking about possible futures, preparedness and adaptation. In this paper we show how this alternative approach of using a hydrological model has benefits and we discuss the limitations and lessons of the approach for future interdisciplinary research.

HESS Opinions Catchments as meta-organisms – a new blueprint for hydrological modelling

Abstract. Catchment-scale hydrological models frequently miss essential characteristics of what determines the functioning of catchments. The most important active agent in catchments is the ecosystem. It manipulates and partitions moisture in a way that supports the essential functions of survival and productivity: infiltration of water, retention of moisture, mobilization and retention of nutrients, and drainage. Ecosystems do this in the most efficient way, establishing a continuous, ever-evolving feedback loop with the landscape and climatic drivers. In brief, hydrological systems are alive and have a strong capacity to adjust themselves to prevailing and changing environmental conditions. Although most models take Newtonian theory at heart, as best they can, what they generally miss is Darwinian theory on how an ecosystem evolves and adjusts its environment to maintain crucial hydrological functions. In addition, catchments, such as many other natural systems, do not only evolve over time, but develop features of spatial organization, including surface or sub-surface drainage patterns, as a by-product of this evolution. Models that fail to account for patterns and the associated feedbacks miss a critical element of how systems at the interface of atmosphere, biosphere and pedosphere function. In contrast to what is widely believed, relatively simple, semi-distributed conceptual models have the potential to accommodate organizational features and their temporal evolution in an efficient way, a reason for that being that because their parameters (and their evolution over time) are effective at the modelling scale, and thus integrate natural heterogeneity within the system, they may be directly inferred from observations at the same scale, reducing the need for calibration and related problems. In particular, the emergence of new and more detailed observation systems from space will lead towards a more robust understanding of spatial organization and its evolution. This will further permit the development of relatively simple time-dynamic functional relationships that can meaningfully represent spatial patterns and their evolution over time, even in poorly gauged environments.

Rapid surface-water volume estimations in beaver ponds

Abstract. Beaver ponds are surface-water features that are transient through space and time. Such qualities complicate the inclusion of beaver ponds in local and regional water balances, and in hydrological models, as reliable estimates of surface-water storage are difficult to acquire without time- and labour-intensive topographic surveys. A simpler approach to overcome this challenge is needed, given the abundance of the beaver ponds in North America, Eurasia, and southern South America. We investigated whether simple morphometric characteristics derived from readily available aerial imagery or quickly measured field attributes of beaver ponds can be used to approximate surface-water storage among the range of environmental settings in which beaver ponds are found. Studied were a total of 40 beaver ponds from four different sites in North and South America. The simplified volume–area–depth (V–A–h) approach, originally developed for prairie potholes, was tested. With only two measurements of pond depth and corresponding surface area, this method estimated surface-water storage in beaver ponds within 5 % on average. Beaver pond morphometry was characterized by a median basin coefficient of 0.91, and dam length and pond surface area were strongly correlated with beaver pond storage capacity, regardless of geographic setting. These attributes provide a means for coarsely estimating surface-water storage capacity in beaver ponds. Overall, this research demonstrates that reliable estimates of surface-water storage in beaver ponds only requires simple measurements derived from aerial imagery and/or brief visits to the field. Future research efforts should be directed at incorporating these simple methods into both broader beaver-related tools and catchment-scale hydrological models.

Erratum to: A comparison of changes in river runoff from multiple global and catchment-scale hydrological models under global warming scenarios of 1 °C, 2 °C and 3 °C

A comparison of changes in river runoff from multiple global and catchment-scale hydrological models under global warming scenarios of 1 degrees C, 2 degrees C and 3 degrees C (vol 141, pg 577, 2017)

A comparison of changes in river runoff from multiple global and catchment-scale hydrological models under global warming scenarios of 1\xa0\xb0C, 2\xa0\xb0C and 3\xa0\xb0C

We present one of the first climate change impact assessments on river runoff that utilises an ensemble of global hydrological models (Glob-HMs) and an ensemble of catchment-scale hydrological models (Cat-HMs), across multiple catchments: the upper Amazon, Darling, Ganges, Lena, upper Mississippi, upper Niger, Rhine and Tagus. Relative changes in simulated mean annual runoff (MAR) and four indicators of high and low extreme flows are compared between the two ensembles. The ensemble median values of changes in runoff with three different scenarios of global-mean warming (1, 2 and 3 °C above pre-industrial levels) are generally similar between the two ensembles, although the ensemble spread is often larger for the Glob-HM ensemble. In addition the ensemble spread is normally larger than the difference between the two ensemble medians. Whilst we find compelling evidence for projected runoff changes for the Rhine (decrease), Tagus (decrease) and Lena (increase) with global warming, the sign and magnitude of change for the other catchments is unclear. Our model results highlight that for these three catchments in particular, global climate change mitigation, which limits global-mean temperature rise to below 2 °C above preindustrial levels, could avoid some of the hydrological hazards that could be seen with higher magnitudes of global warming.

The importance of hydraulic groundwater theory in catchment hydrology: The legacy of Wilfried Brutsaert and Jean-Yves Parlange

Based on a literature overview, this paper summarizes the impact and legacy of the contributions of Wilfried Brutsaert and Jean-Yves Parlange (Cornell University) with respect to the current state-of-the-art understanding in hydraulic groundwater theory. Forming the basis of many applications in catchment hydrology, ranging from drought flow analysis to surface water-groundwater interactions, hydraulic groundwater theory simplifies the description of water flow in unconfined riparian and perched aquifers through assumptions attributed to Dupuit and Forchheimer. Boussinesq (1877) derived a general equation to study flow dynamics of unconfined aquifers in uniformly sloping hillslopes, resulting in a remarkably accurate and applicable family of results, though often challenging to solve due to its nonlinear form. Under certain conditions, the Boussinesq equation can be solved analytically allowing compact representation of soil and geomorphological controls on unconfined aquifer storage and release dynamics. The Boussinesq equation has been extended to account for flow divergence/convergence as well as for nonuniform bedrock slope (concave/convex). The extended Boussinesq equation has been favorably compared to numerical solutions of the three-dimensional Richards equation, confirming its validity under certain geometric conditions. Analytical solutions of the linearized original and extended Boussinesq equations led to the formulation of similarity indices for baseflow recession analysis, including scaling rules, to predict the moments of baseflow response. Validation of theoretical recession parameters on real-world streamflow data is complicated due to limited measurement accuracy, changing boundary conditions, and the strong coupling between the saturated aquifer with the overlying unsaturated zone. However, recent advances are shown to have mitigated several of these issues. The extended Boussinesq equation has been successfully applied to represent baseflow dynamics in catchment-scale hydrological models, and it is currently considered to represent lateral redistribution of groundwater in land surface schemes applied in global circulation models. From the review, it is clear that Wilfried Brutsaert and Jean-Yves Parlange stimulated a body of research that has led to several fundamental discoveries and practical applications with important contributions in hydrological modeling.

Effect of modelling scale on the assessment of climate change impact on river runoff

The effect of using two distributed hydrological models with different degrees of spatial aggregation on the assessment of climate change impact on river runoff was investigated. Analyses were conducted in the Narew River basin situated in northeast Poland using a global hydrological model (WaterGAP) and a catchment-scale hydrological model (SWAT). Climate change was represented in both models by projected changes in monthly temperature and precipitation between the period 2040–2069 and the baseline period, resulting from two general circulation models: IPSL-CM4 and MIROC3.2, both coupled with the SRES A2 emissions scenario. The degree of consistency between the global and the catchment model was very high for mean annual runoff, and medium for indicators of high and low runoff. It was observed that SWAT generally suggests changes of larger magnitude than WaterGAP for both climate models, but SWAT and WaterGAP were consistent as regards the direction of change in monthly runoff. The results indicate that a global model can be used in Central and Eastern European lowlands to identify hot-spots where a catchment-scale model should be applied to evaluate, e.g. the effectiveness of management options. Editor D. Koutsoyiannis; Associate editor F.F. Hattermann Citation Piniewski, M., Voss, F., Bärlund, I., Okruszko, T., and Kundzewicz. Z.W., 2013. Effect of modelling scale on the assessment of climate change impact on river runoff. Hydrological Sciences Journal, 58 (4), 737–754.

A watershed rainfall data recovery approach with application to distributed hydrological models

Watershed areal rainfall estimation, which is one of the most important and fundamental aspects in hydrological forecasting and various kinds of catchment-scale hydrological models, is widely used in the analysis of hydrological regime change, and its precision has a direct influence on the accuracy of hydrological forecasting and hydrological simulation. In China, it is difficult to obtain the watershed areal rainfall estimate with reliable precision and avoid the phenomenon of ‘the same effect of different parameters’ because of the low density of the rain gauge network. Therefore, a watershed rainfall data recovery approach of improving the precision of watershed areal rainfall estimation is proposed here. This approach is to build new observatories, establish the time–space relations of rainfall between newly built observatories and previously built observatories in a relatively short interval and then recover the rainfall data of newly built observatories prior to their construction through simulating the relations over a longer time. As a result, watershed rainfall information could be elaborated to improve the precision of watershed areal rainfall estimate and avoid the phenomenon of ‘the same effect of different parameters’ to a certain degree in the process of hydrological simulation. The approach is used in the hydrological simulation of Hali River catchment. In combination with the Soil Water Assessment Tool model, a better result can be obtained in the hydrological simulation. Therefore, the approach can be used in other similar catchments. Copyright © 2011 John Wiley & Sons, Ltd.

A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

Abstract. We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and developmental conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangxi (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs include SLURP v. 12.2 (Liard), SLURP v. 12.7 (Mekong), Pitman (Okavango), MGB-IPH (Rio Grande), AV-SWAT-X 2005 (Xiangxi) and Cat-PDM (Harper's Brook). The CHMs typically simulate water resource impacts based on a more explicit representation of catchment water resources than that available from the GHM and the CHMs include river routing, whereas the GHM does not. Simulations of mean annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961–1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global-mean air temperature of 1.0, 2.0, 3.0, 4.0, 5.0 and 6.0 °C relative to baseline from the UKMO HadCM3 Global Climate Model (GCM) to explore response to different amounts of climate forcing, and (2) a prescribed increase in global-mean air temperature of 2.0 °C relative to baseline for seven GCMs to explore response to climate model structural uncertainty. We find that the differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM (e.g. an absolute GHM-CHM difference in mean annual runoff percentage change for UKMO HadCM3 2 °C warming of up to 25%), and they are generally larger for indicators of high and low monthly runoff. However, they are relatively small in comparison to the range of projections across the seven GCMs. Hence, for the six catchments and seven GCMs we considered, climate model structural uncertainty is greater than the uncertainty associated with the type of hydrological model applied. Moreover, shifts in the seasonal cycle of runoff with climate change are represented similarly by both hydrological models, although for some catchments the monthly timing of high and low flows differs. This implies that for studies that seek to quantify and assess the role of climate model uncertainty on catchment-scale runoff, it may be equally as feasible to apply a GHM (Mac-PDM.09 here) as it is to apply a CHM, especially when climate modelling uncertainty across the range of available GCMs is as large as it currently is. Whilst the GHM is able to represent the broad climate change signal that is represented by the CHMs, we find however, that for some catchments there are differences between GHMs and CHMs in mean annual runoff due to differences in potential evapotranspiration estimation methods, in the representation of the seasonality of runoff, and in the magnitude of changes in extreme (Q5, Q95) monthly runoff, all of which have implications for future water management issues.

Data assimilation for distributed hydrological catchment modeling via ensemble Kalman filter

Catchment scale hydrological models are critical decision support tools for water resources management and environment remediation. However, the reliability of hydrological models is inevitably affected by limited measurements and imperfect models. Data assimilation techniques combine complementary information from measurements and models to enhance the model reliability and reduce predictive uncertainties. As a sequential data assimilation technique, the ensemble Kalman filter (EnKF) has been extensively studied in the earth sciences for assimilating in-situ measurements and remote sensing data. Although the EnKF has been demonstrated in land surface data assimilations, there are no systematic studies to investigate its performance in distributed modeling with high dimensional states and parameters. In this paper, we present an assessment on the EnKF with state augmentation for combined state-parameter estimation on the basis of a physical-based hydrological model, Soil and Water Assessment Tool (SWAT). Through synthetic simulation experiments, the capability of the EnKF is demonstrated by assimilating the runoff and other measurements, and its sensitivities are analyzed with respect to the error specification, the initial realization and the ensemble size. It is found that the EnKF provides an efficient approach for obtaining a set of acceptable model parameters and satisfactory runoff, soil water content and evapotranspiration estimations. The EnKF performance could be improved after augmenting with other complementary data, such as soil water content and evapotranspiration from remote sensing retrieval. Sensitivity studies demonstrate the importance of consistent error specification and the potential with small ensemble size in the data assimilation system.

Predicting daily streamflow in ungauged rural catchments: the case of Masinga catchment, Kenya

Access to daily streamflow data at the catchment scale, is a central component of many aspects of water resources and water quality management. However, the majority of river reaches in many catchments in Kenya are ungauged or poorly gauged, and in some cases existing measurement networks are declining. Long-term continuous monitoring is not being done due to high costs of equipment maintenance. Therefore, there is a need for an alternative tool such as a catchment-scale hydrological model that is capable of predicting the daily streamflow. An approach is presented of predicting daily streamflow using a physically-based catchment-scale model, the geospatial Stream Flow Model (SFM). The SFM was developed using the “C” programming language and the user interface was developed using the Avenue script of the ArcView software. The SFM simulates the dynamics of runoff processes by utilizing remotely sensed and widely available global or local data sets. The model was applied in the Masinga catchment, Kenya, and the results gave a model performance coefficient of 0.74 based on the Nash-Sutcliffe statistical criterion.