Showing papers in "Hydrology and Earth System Sciences in 2012"

Technical Note: Downscaling RCM precipitation to the station scale using statistical transformations – a comparison of methods

Abstract: The impact of climate change on water resources is usually assessed at the local scale. However, regional climate models (RCMs) are known to exhibit systematic biases in precipitation. Hence, RCM simulations need to be post-processed in order to produce reliable estimates of local scale climate. Popular post-processing approaches are based on statistical transformations, which attempt to adjust the distribution of modelled data such that it closely resembles the observed climatology. However, the diversity of suggested methods renders the selection of optimal techniques difficult and therefore there is a need for clarification. In this paper, statistical transformations for post-processing RCM output are reviewed and classified into (1) distribution derived transformations, (2) parametric transformations and (3) nonparametric transformations, each differing with respect to their underlying assumptions. A real world application, using observations of 82 precipitation stations in Norway, showed that nonparametric transformations have the highest skill in systematically reducing biases in RCM precipitation.

HESS Opinions "Should we apply bias correction to global and regional climate model data?"

Abstract: Despite considerable progress in recent years, output of both global and regional circulation models is still afflicted with biases to a degree that precludes its direct use, especially in climate change impact studies. This is well known, and to overcome this problem, bias correction (BC; i.e. the correction of model output towards observations in a post-processing step) has now become a standard procedure in climate change impact studies. In this paper we argue that BC is currently often used in an invalid way: it is added to the GCM/RCM model chain without sufficient proof that the consistency of the latter (i.e. the agreement between model dynamics/model output and our judgement) as well as the generality of its applicability increases. BC methods often impair the advantages of circulation models by altering spatiotemporal field consistency, relations among variables and by violating conservation principles. Currently used BC methods largely neglect feedback mechanisms, and it is unclear whether they are time-invariant under climate change conditions. Applying BC increases agreement of climate model output with observations in hindcasts and hence narrows the uncertainty range of simulations and predictions without, however, providing a satisfactory physical justification. This is in most cases not transparent to the end user. We argue that this hides rather than reduces uncertainty, which may lead to avoidable forejudging of end users and decision makers. We present here a brief overview of state-of-the-art bias correction methods, discuss the related assumptions and implications, draw conclusions on the validity of bias correction and propose ways to cope with biased output of circulation models in the short term and how to reduce the bias in the long term. The most promising strategy for improved future global and regional circulation model simulations is the increase in model resolution to the convection-permitting scale in combination with ensemble predictions based on sophisticated approaches for ensemble perturbation. With this article, we advocate communicating the entire uncertainty range associated with climate change predictions openly and hope to stimulate a lively discussion on bias correction among the atmospheric and hydrological community and end users of climate change impact studies.

COSMOS: the COsmic-ray Soil Moisture Observing System

Abstract: The newly-developed cosmic-ray method for mea- suring area-average soil moisture at the hectometer horizon- tal scale is being implemented in the COsmic-ray Soil Mois- ture Observing System (or the COSMOS). The stationary cosmic-ray soil moisture probe measures the neutrons that are generated by cosmic rays within air and soil and other materials, moderated by mainly hydrogen atoms located pri- marily in soil water, and emitted to the atmosphere where they mix instantaneously at a scale of hundreds of meters and whose density is inversely correlated with soil moisture. The COSMOS has already deployed more than 50 of the even- tual 500 cosmic-ray probes, distributed mainly in the USA, each generating a time series of average soil moisture over its horizontal footprint, with similar networks coming into exis- tence around the world. This paper is written to serve a com- munity need to better understand this novel method and the COSMOS project. We describe the cosmic-ray soil moisture measurement method, the instrument and its calibration, the design, data processing and dissemination used in the COS- MOS project, and give example time series of soil moisture obtained from COSMOS probes.

Teaching hydrological modeling with a user-friendly catchment-runoff-model software package

Abstract: Computer models, especially conceptual models, are frequently used for catchment hydrology studies. Teaching hydrological modeling, however, is challenging, since students have to both understand general model concepts and be able to use particular computer programs when learning to apply computer models. Here we present a new version of the HBV ( Hydrologiska Byrans Vattenavdelning ) model. This software provides a user-friendly version that is especially useful for education. Different functionalities, such as an automatic calibration using a genetic algorithm or a Monte Carlo approach, as well as the possibility to perform batch runs with predefined model parameters make the software interesting especially for teaching in more advanced classes and research projects. Different teaching goals related to hydrological modeling are discussed and a series of exercises is suggested to reach these goals.

Technical Note: Bias correcting climate model simulated daily temperature extremes with quantile mapping

Abstract: . When applying a quantile mapping-based bias correction to daily temperature extremes simulated by a global climate model (GCM), the transformed values of maximum and minimum temperatures are changed, and the diurnal temperature range (DTR) can become physically unrealistic. While causes are not thoroughly explored, there is a strong relationship between GCM biases in snow albedo feedback during snowmelt and bias correction resulting in unrealistic DTR values. We propose a technique to bias correct DTR, based on comparing observations and GCM historic simulations, and combine that with either bias correcting daily maximum temperatures and calculating daily minimum temperatures or vice versa. By basing the bias correction on a base period of 1961–1980 and validating it during a test period of 1981–1999, we show that bias correcting DTR and maximum daily temperature can produce more accurate estimations of daily temperature extremes while avoiding the pathological cases of unrealistic DTR values.

Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities

Abstract: Data assimilation (DA) holds considerable potential for improving hydrologic predictions as demonstrated in numerous research studies. However, advances in hydrologic DA research have not been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. This is due in part to a lack of mechanisms to properly quantify the uncertainty in observations and forecast models in real-time forecasting situations and to conduct the merging of data and models in a way that is adequately efficient and transparent to operational forecasters. The need for effective DA of useful hydrologic data into the forecast process has become increasingly recognized in recent years. This motivated a hydrologic DA workshop in Delft, the Netherlands in November 2010, which focused on advancing DA in operational hydrologic forecasting and water resources management. As an outcome of the workshop, this paper reviews, in relevant detail, the current status of DA applications in both hydrologic research and operational practices, and discusses the existing or potential hurdles and challenges in transitioning hydrologic DA research into cost-effective operational forecasting tools, as well as the potential pathways and newly emerging opportunities for overcoming these challenges. Several related aspects are discussed, including (1) theoretical or mathematical aspects in DA algorithms, (2) the estimation of different types of uncertainty, (3) new observations and their objective use in hydrologic DA, (4) the use of DA for real-time control of water resources systems, and (5) the development of community-based, generic DA tools for hydrologic applications. It is recommended that cost-effective transition of hydrologic DA from research to operations should be helped by developing community-based, generic modeling and DA tools or frameworks, and through fostering collaborative efforts among hydrologic modellers, DA developers, and operational forecasters.

A process-based typology of hydrological drought

Abstract: Hydrological drought events have very differ- ent causes and effects. Classifying these events into dis- tinct types can be useful for both science and manage- ment. We propose a hydrological drought typology that is based on governing drought propagation processes de- rived from catchment-scale drought analysis. In this ty- pology six hydrological drought types are distinguished, i.e. (i) classical rainfall deficit drought, (ii) rain-to-snow- season drought, (iii) wet-to-dry-season drought, (iv) cold snow season drought, (v) warm snow season drought , and (vi) composite drought. The processes underlying these drought types are the result of the interplay of temperature and precipitation at catchment scale in different seasons. As a test case, about 125 groundwater droughts and 210 dis- charge droughts in five contrasting headwater catchments in Europe have been classified. The most common drought type in all catchments was the classical rainfall deficit drought (almost 50 % of all events), but in the selected catchments these were mostly minor events. If only the five most severe drought events of each catchment are considered, a shift to- wards more rain-to-snow-season droughts , warm snow sea- son droughts, and composite droughts was found. The oc- currence of hydrological drought types is determined by cli- mate and catchment characteristics. The drought typology is transferable to other catchments, including outside Europe, because it is generic and based upon processes that occur around the world. A general framework is proposed to iden- tify drought type occurrence in relation to climate and catch- ment characteristics.

Future changes in Mekong River hydrology: impact of climate change and reservoir operation on discharge

Abstract: . The transboundary Mekong River is facing two ongoing changes that are expected to significantly impact its hydrology and the characteristics of its exceptional flood pulse. The rapid economic development of the riparian countries has led to massive plans for hydropower construction, and projected climate change is expected to alter the monsoon patterns and increase temperature in the basin. The aim of this study is to assess the cumulative impact of these factors on the hydrology of the Mekong within next 20–30 yr. We downscaled the output of five general circulation models (GCMs) that were found to perform well in the Mekong region. For the simulation of reservoir operation, we used an optimisation approach to estimate the operation of multiple reservoirs, including both existing and planned hydropower reservoirs. For the hydrological assessment, we used a distributed hydrological model, VMod, with a grid resolution of 5 km × 5 km. In terms of climate change's impact on hydrology, we found a high variation in the discharge results depending on which of the GCMs is used as input. The simulated change in discharge at Kratie (Cambodia) between the baseline (1982–1992) and projected time period (2032–2042) ranges from −11% to p15% for the wet season and −10% to p13% for the dry season. Our analysis also shows that the changes in discharge due to planned reservoir operations are clearly larger than those simulated due to climate change: 25–160% higher dry season flows and 5–24% lower flood peaks in Kratie. The projected cumulative impacts follow rather closely the reservoir operation impacts, with an envelope around them induced by the different GCMs. Our results thus indicate that within the coming 20–30 yr, the operation of planned hydropower reservoirs is likely to have a larger impact on the Mekong hydrograph than the impacts of climate change, particularly during the dry season. On the other hand, climate change will increase the uncertainty of the estimated reservoir operation impacts: our results indicate that even the direction of the flow-related changes induced by climate change is partly unclear. Consequently, both dam planners and dam operators should pay closer attention to the cumulative impacts of climate change and reservoir operation on aquatic ecosystems, including the multibillion-dollar Mekong fisheries.

Dryland ecohydrology and climate change: critical issues and technical advances

Abstract: Drylands cover about 40 % of the terrestrial land surface and account for approximately 40 % of global net primary productivity. Water is fundamental to the biophys- ical processes that sustain ecosystem function and food pro- duction, particularly in drylands where a tight coupling ex- ists between ecosystem productivity, surface energy balance, biogeochemical cycles, and water resource availability. Cur- rently, drylands support at least 2 billion people and comprise both natural and managed ecosystems. In this synthesis, we identify some current critical issues in the understanding of dryland systems and discuss how arid and semiarid environ- ments are responding to the changes in climate and land use. The issues range from societal aspects such as rapid popu- lation growth, the resulting food and water security, and de- velopment issues, to natural aspects such as ecohydrological consequences of bush encroachment and the causes of de- sertification. To improve current understanding and inform upon the needed research efforts to address these critical is- sues, we identify some recent technical advances in terms of monitoring dryland water dynamics, water budget and veg- etation water use, with a focus on the use of stable isotopes and remote sensing. These technological advances provide new tools that assist in addressing critical issues in dryland ecohydrology under climate change.

The blue water footprint of electricity from hydropower

Abstract: Hydropower accounts for about 16 % of the world's electricity supply. It has been debated whether hy- droelectric generation is merely an in-stream water user or whether it also consumes water. In this paper we provide scientific support for the argument that hydroelectric genera- tion is in most cases a significant water consumer. The study assesses the blue water footprint of hydroelectricity - the wa- ter evaporated from manmade reservoirs to produce electric energy - for 35 selected sites. The aggregated blue water footprint of the selected hydropower plants is 90 Gm 3 yr 1 , which is equivalent to 10 % of the blue water footprint of global crop production in the year 2000. The total blue wa- ter footprint of hydroelectric generation in the world must be considerably larger if one considers the fact that this study covers only 8 % of the global installed hydroelectric capacity. Hydroelectric generation is thus a significant water consumer. The average water footprint of the selected hy- dropower plants is 68 m 3 GJ 1 . Great differences in water footprint among hydropower plants exist, due to differences in climate in the places where the plants are situated, but more importantly as a result of large differences in the area flooded per unit of installed hydroelectric capacity. We rec- ommend that water footprint assessment is added as a com- ponent in evaluations of newly proposed hydropower plants as well as in the evaluation of existing hydroelectric dams, so that the consequences of the water footprint of hydroelec- tric generation on downstream environmental flows and other water users can be evaluated.

Spatial and temporal variability of rainfall erosivity factor for Switzerland

Abstract: . Rainfall erosivity, considering rainfall amount and intensity, is an important parameter for soil erosion risk assessment under future land use and climate change. Despite its importance, rainfall erosivity is usually implemented in models with a low spatial and temporal resolution. The purpose of this study is to assess the temporal- and spatial distribution of rainfall erosivity in form of the (Revised) Universal Soil Loss Equation R-factor for Switzerland. Time series of 22 yr for rainfall (10 min resolution) and temperature (1 h resolution) data were analysed for 71 automatic gauging stations distributed throughout Switzerland. Regression-kriging was used to interpolate the rainfall erosivity values of single stations and to generate a map for Switzerland. Latitude, longitude, average annual precipitation, biogeographic units (Jura, Midland, etc.), aspect and elevation were used as covariates, of which average annual precipitation, elevation and the biographic unit (Western Central Alps) were significant (p

SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds – the two-CN system approach

Abstract: The Soil Conservation Service Curve Number (SCS-CN) approach is widely used as a simple method for predicting direct runoff volume for a given rainfall event. The CN parameter values corresponding to various soil, land cover, and land management conditions can be selected from tables, but it is preferable to estimate the CN value from measured rainfall-runoff data if available. However, previous researchers indicated that the CN values calculated from measured rainfall-runoff data vary systematically with the rainfall depth. Hence, they suggested the determination of a single asymptotic CN value observed for very high rainfall depths to characterize the watersheds' runoff response. In this paper, the hypothesis that the observed correlation between the calculated CN value and the rainfall depth in a watershed reflects the effect of soils and land cover spatial variability on its hydrologic response is being tested. Based on this hypothesis, the simplified concept of a two-CN heterogeneous system is introduced to model the observed CN-rainfall variation by reducing the CN spatial variability into two classes. The behaviour of the CN-rainfall function produced by the simplified two-CN system is approached theoretically, it is analysed systematically, and it is found to be similar to the variation observed in natural watersheds. Synthetic data tests, natural watersheds examples, and detailed study of two natural experimental watersheds with known spatial heterogeneity characteristics were used to evaluate the method. The results indicate that the determination of CN values from rainfall runoff data using the proposed two-CN system approach provides reasonable accuracy and it over performs the previous methods based on the determination of a single asymptotic CN value. Although the suggested method increases the number of unknown parameters to three (instead of one), a clear physical reasoning for them is presented.

The Indus basin in the framework of current and future water resources management

Abstract: . The Indus basin is one of the regions in the world that is faced with major challenges for its water sector, due to population growth, rapid urbanisation and industrialisation, environmental degradation, unregulated utilization of the resources, inefficient water use and poverty, all aggravated by climate change. The Indus Basin is shared by 4 countries – Pakistan, India, Afghanistan and China. With a current population of 237 million people which is projected to increase to 319 million in 2025 and 383 million in 2050, already today water resources are abstracted almost entirely (more than 95% for irrigation). Climate change will result in increased water availability in the short term. However in the long term water availability will decrease. Some current aspects in the basin need to be re-evaluated. During the past decades water abstractions – and especially groundwater extractions – have augmented continuously to support a rice-wheat system where rice is grown during the kharif (wet, summer) season (as well as sugar cane, cotton, maize and other crops) and wheat during the rabi (dry, winter) season. However, the sustainability of this system in its current form is questionable. Additional water for domestic and industrial purposes is required for the future and should be made available by a reduction in irrigation requirements. This paper gives a comprehensive listing and description of available options for current and future sustainable water resources management (WRM) within the basin. Sustainable WRM practices include both water supply management and water demand management options. Water supply management options include: (1) reservoir management as the basin is characterised by a strong seasonal behaviour in water availability (monsoon and meltwater) and water demands; (2) water quality conservation and investment in wastewater infrastructure; (3) the use of alternative water resources like the recycling of wastewater and desalination; (4) land use planning and soil conservation as well as flood management, with a focus on the reduction of erosion and resulting sedimentation as well as the restoration of ecosystem services like wetlands and natural floodplains. Water demand management options include: (1) the management of conjunctive use of surface and groundwater; as well as (2) the rehabilitation and modernization of existing infrastructure. Other demand management options are: (3) the increase of water productivity for agriculture; (4) crop planning and diversification including the critical assessment of agricultural export, especially (basmati) rice; (5) economic instruments and (6) changing food demand patterns and limiting post-harvest losses.

Assessing water footprint at river basin level: a case study for the Heihe River Basin in northwest China

Abstract: Increasing water scarcity places considerable importance on the quantification of water footprint (WF) at different levels. Despite progress made previously, there are still very few WF studies focusing on specific river basins, especially for those in arid and semi-arid regions. The aim of this study is to quantify WF within the Heihe River Basin (HRB), a basin located in the arid and semi-arid northwest of China. The findings show that the WF was 1768 million m3 yr−1 in the HRB over 2004–2006. Agricultural production was the largest water consumer, accounting for 96% of the WF (92% for crop production and 4% for livestock production). The remaining 4% was for the industrial and domestic sectors. The "blue" (surface- and groundwater) component of WF was 811 million m3 yr−1. This indicates a blue water proportion of 46%, which is much higher than the world average and China's average, which is mainly due to the aridness of the HRB and a high dependence on irrigation for crop production. However, even in such a river basin, blue WF was still smaller than "green" (soil water) WF, indicating the importance of green water. We find that blue WF exceeded blue water availability during eight months per year and also on an annual basis. This indicates that WF of human activities was achieved at a cost of violating environmental flows of natural freshwater ecosystems, and such a WF pattern is not sustainable. Considering the large WF of crop production, optimizing the crop planting pattern is often a key to achieving more sustainable water use in arid and semi-arid regions

Regional effects of vegetation restoration on water yield across the Loess Plateau, China

Abstract: The general relationships between vegetation and water yield under different climatic regimes are well estab- lished at a small watershed scale in the past century. How- ever, applications of these basic theories to evaluate the re- gional effects of land cover change on water resources re- main challenging due to the complex interactions of vegeta- tion and climatic variability and hydrologic processes at the large scale. The objective of this study was to explore ways to examine the spatial and temporal effects of a large eco- logical restoration project on water yield across the Loess Plateau region in northern China. We estimated annual water yield as the difference between precipitation input and mod- elled actual evapotranspiration (ET) output. We constructed a monthly ET model using published ET data derived from eddy flux measurements and watershed streamflow data. We validated the ET models at a watershed and regional levels. The model was then applied to examine regional water yield under land cover change and climatic variability during the implementation of the Grain-for-Green (GFG) project during 1999-2007. We found that water yield in 38 % of the Loess Plateau area might have decreased (1-48 mm per year) as a result of land cover change alone. However, combined with climatic variability, 37 % of the study area might have seen a decrease in water yield with a range of 1-54 mm per year, and 35 % of the study area might have seen an increase with a range of 1-10 mm per year. Across the study region, cli- mate variability masked or strengthened the water yield re- sponse to vegetation restoration. The absolute annual water yield change due to vegetation restoration varied with pre- cipitation regimes with the highest in wet years, but the rela- tive water yield changes were most pronounced in dry years. We concluded that the effects of land cover change associ- ated with ecological restoration varied greatly over time and space and were strongly influenced by climatic variability in the arid region. The current regional vegetation restoration projects have variable effects on local water resources across the region. Land management planning must consider the in- fluences of spatial climate variability and long-term climate change on water yield to be more effective for achieving en- vironmental sustainability.

Analysis of parameter uncertainty in hydrological and sediment modeling using GLUE method: a case study of SWAT model applied to Three Gorges Reservoir Region, China

Abstract: . The calibration of hydrologic models is a worldwide challenge due to the uncertainty involved in the large number of parameters. The difficulty even increases in a region with high seasonal variation of precipitation, where the results exhibit high heteroscedasticity and autocorrelation. In this study, the Generalized Likelihood Uncertainty Estimation (GLUE) method was combined with the Soil and Water Assessment Tool (SWAT) to quantify the parameter uncertainty of the stream flow and sediment simulation in the Daning River Watershed of the Three Gorges Reservoir Region (TGRA), China. Based on this study, only a few parameters affected the final simulation output significantly. The results showed that sediment simulation presented greater uncertainty than stream flow, and uncertainty was even greater in high precipitation conditions (from May to September) than during the dry season. The main uncertainty sources of stream flow came from the catchment process while a channel process impacts the sediment simulation greatly. It should be noted that identifiable parameters such as CANMX, ALPHA_BNK, SOL_K could be obtained with an optimal parameter range using calibration method. However, equifinality was also observed in hydrologic modeling in TGRA. This study demonstrated that care must be taken when calibrating the SWAT model with non-identifiable parameters because these may lead to equifinality of the parameter values. It was anticipated this study would provide useful information for hydrology modeling related to policy development in the Three Gorges Reservoir Region (TGRA) and other similar areas.

Partitioning of evaporation into transpiration, soil evaporation and interception: a comparison between isotope measurements and a HYDRUS-1D model

Abstract: Knowledge of the water fluxes within the soil-vegetation-atmosphere system is crucial to improve water use efficiency in irrigated land. Many studies have tried to quantify these fluxes, but they encountered difficulties in quantifying the relative contribution of evaporation and transpiration. In this study, we compared three different methods to estimate evaporation fluxes during simulated summer conditions in a grass-covered lysimeter in the laboratory. Only two of these methods can be used to partition total evaporation into transpiration, soil evaporation and interception. A water balance calculation (whereby rainfall, soil moisture and percolation were measured) was used for comparison as a benchmark. A HYDRUS-1D model and isotope measurements were used for the partitioning of total evaporation. The isotope mass balance method partitions total evaporation of 3.4 mm d?1 into 0.4 mm d?1 for soil evaporation, 0.3 mm d?1 for interception and 2.6 mm d?1 for transpiration, while the HYDRUS-1D partitions total evaporation of 3.7 mm d?1 into 1 mm d?1 for soil evaporation, 0.3 mm d?1 for interception and 2.3 mm d?1 for transpiration. From the comparison, we concluded that the isotope mass balance is better for low temporal resolution analysis than the HYDRUS-1D. On the other hand, HYDRUS-1D is better for high temporal resolution analysis than the isotope mass balance.

Water resources trends in Middle East and North Africa towards 2050

Abstract: Changes in water resources availability can be expected as consequences of climate change, population growth, economic development and environmental considerations. A two-stage modeling approach is used to explore the impact of these changes in the Middle East and North Africa (MENA) region. An advanced, physically based, distributed, hydrological model is applied to determine the internal and external renewable water resources for the current situation and under future changes. Subsequently, a water allocation model is used to combine the renewable water resources with sectoral water demands. Results show that total demand in the region will increase to 393 km3 yr−1 in 2050, while total water shortage will grow to 199 km3 yr−1 in 2050 for the average climate change projection, an increase of 157 km3 yr−1. This increase in shortage is the combined impact of an increase in water demand by 50 percent with a decrease in water supply by 12 percent. Uncertainty, based on the output of the nine GCMs applied, reveals that expected water shortage ranges from 85 km3 yr−1 to 283 km3 yr−1 in 2050. The analysis shows that 22 percent of the water shortage can be attributed to climate change and 78 percent to changes in socioeconomic factors.

Deriving global flood hazard maps of fluvial floods through a physical model cascade

Abstract: . Global flood hazard maps can be used in the assessment of flood risk in a number of different applications, including (re)insurance and large scale flood preparedness. Such global hazard maps can be generated using large scale physically based models of rainfall-runoff and river routing, when used in conjunction with a number of post-processing methods. In this study, the European Centre for Medium Range Weather Forecasts (ECMWF) land surface model is coupled to ERA-Interim reanalysis meteorological forcing data, and resultant runoff is passed to a river routing algorithm which simulates floodplains and flood flow across the global land area. The global hazard map is based on a 30 yr (1979–2010) simulation period. A Gumbel distribution is fitted to the annual maxima flows to derive a number of flood return periods. The return periods are calculated initially for a 25 × 25 km grid, which is then reprojected onto a 1 × 1 km grid to derive maps of higher resolution and estimate flooded fractional area for the individual 25 × 25 km cells. Several global and regional maps of flood return periods ranging from 2 to 500 yr are presented. The results compare reasonably to a benchmark data set of global flood hazard. The developed methodology can be applied to other datasets on a global or regional scale.

A simple three-dimensional macroscopic root water uptake model based on the hydraulic architecture approach

Abstract: Many hydrological models including root water uptake (RWU) do not consider the dimension of root system hydraulic architecture (HA) because explicitly solving water flow in such a complex system is too time consuming. However, they might lack process understanding when basing RWU and plant water stress predictions on functions of variables such as the root length density distribution. On the basis of analytical solutions of water flow in a simple HA, we developed an “implicit” model of the root system HA for simulation of RWU distribution (sink term of Richards’ equation) and plant water stress in three-dimensional soil water flow models. The new model has three macroscopic parameters defined at the soil element scale, or at the plant scale, rather than for each segment of the root system architecture: the standard sink fraction distribution SSF, the root system equivalent conductanceKrs and the compensatory RWUconductance Kcomp. It clearly decouples the process of water stress from compensatory RWU, and its structure is appropriate for hydraulic lift simulation. As compared to a model explicitly solving water flow in a realistic maize root system HA, the implicit model showed to be accurate for predicting RWU distribution and plant collar water potential, with one single set of parameters, in dissimilar water dynamics scenarios. For these scenarios, the computing time of the implicit model was a factor 28 to 214 shorter than that of the explicit one.We also provide a new expression for the effective soil water potential sensed by plants in soils with a heterogeneous water potential distribution, which emerged from the implicit model equations. With the proposed implicit model of the root system HA, new concepts are brought which open avenues towards simple and mechanistic RWU models and water stress functions operational for field scale water dynamics simulation.

HESS Opinions "More efforts and scientific rigour are needed to attribute trends in flood time series"

Abstract: . The question whether the magnitude and frequency of floods have changed due to climate change or other drivers of change is of high interest. The number of flood trend studies is rapidly rising. When changes are detected, many studies link the identified change to the underlying causes, i.e. they attribute the changes in flood behaviour to certain drivers of change. We propose a hypothesis testing framework for trend attribution which consists of essential ingredients for a sound attribution: evidence of consistency, evidence of inconsistency, and provision of confidence statement. Further, we evaluate the current state-of-the-art of flood trend attribution. We assess how selected recent studies approach the attribution problem, and to which extent their attribution statements seem defendable. In our opinion, the current state of flood trend attribution is poor. Attribution statements are mostly based on qualitative reasoning or even speculation. Typically, the focus of flood trend studies is the detection of change, i.e. the statistical analysis of time series, and attribution is regarded as an appendix: (1) flood time series are analysed by means of trend tests, (2) if a significant change is detected, a hypothesis on the cause of change is given, and (3) explanations or published studies are sought which support the hypothesis. We believe that we need a change in perspective and more scientific rigour: detection should be seen as an integral part of the more challenging attribution problem, and detection and attribution should be placed in a sound hypothesis testing framework.

Critical review of SWAT applications in the upper Nile basin countries

Abstract: The Soil and Water Assessment Tool (SWAT) is an integrated river basin model that is widely applied within the Nile basin. Up to date, more than 20 peer-reviewed papers describe the use of SWAT for a variety of problems in the upper Nile basin countries, such as erosion modelling, land use and climate change impact modelling and water resources management. The majority of the studies are focused on locations in the tropical highlands in Ethiopia and around Lake Victoria. The popularity of SWAT is attributed to the fact that the tool is freely available and that it is readily applicable through the development of geographic information system (GIS) based interfaces and its easy linkage to sensitivity, calibration and uncertainty analysis tools. The online and free availability of basic GIS data that are required for SWAT made its applicability more straightforward even in data-scarce areas. However, the easy use of SWAT may not always lead to appropriate models which is also a consequence of the quality of the available free databases in these regions. In this paper, we aim at critically reviewing the use of SWAT in the context of the modelling purpose and problem descriptions in the tropical highlands of the Nile basin countries. To evaluate the models that are described in journal papers, a number of criteria are used to evaluate the model set-up, model performances, physical representation of the model parameters, and the correctness of the hydrological model balance. On the basis of performance indicators, the majority of the SWAT models were classified as giving satisfactory to very good results. Nevertheless, the hydrological mass balances as reported in several papers contained losses that might not be justified. Several papers also reported the use of unrealistic parameter values. More worrying is that many papers lack this information. For this reason, most of the reported SWAT models have to be evaluated critically. An important gap is the lack of attention that is given to the vegetation and crop processes. None of the papers reported any adaptation to the crop parameters, or any crop-related output such as leaf area index, biomass or crop yields. A proper simulation of the land cover is important for obtaining correct runoff generation, evapotranspiration and erosion computations. It is also found that a comparison of SWAT applications on the same or similar case study but by different research teams and/or model versions resulted in very different results. It is therefore recommended to find better methods to evaluate the representativeness of the distributed processes and parameters (especially when land use studies are envisaged) or predictions of the future through environmental changes. The main recommendation is that more details on the model set-up, the parameters and outputs should be provided in the journal papers or supplementary materials in order to allow for a more stringent evaluation of these models.

Quantifying different sources of uncertainty in hydrological projections in an Alpine watershed

Abstract: Many studies have investigated potential climate change impacts on regional hydrology; less attention has been given to the components of uncertainty that affect these scenarios. This study quantifies uncertainties resulting from (i) General Circulation Models (GCMs), (ii) Regional Climate Models (RCMs), (iii) bias-correction of RCMs, and (iv) hydrological model parameterization using a multi-model framework. This consists of three GCMs, three RCMs, three bias-correction techniques, and sets of hydrological model parameters. The study is performed for the Lech watershed (~ 1000 km 2 ), located in the Northern Limestone Alps, Austria. Bias-corrected climate data are used to drive the hydrological model HQsim to simulate runoff under present (1971–2000) and future (2070–2099) climate conditions. Hydrological model parameter uncertainty is assessed by Monte Carlo sampling. The model chain is found to perform well under present climate conditions. However, hydrological projections are associated with high uncertainty, mainly due to the choice of GCM and RCM. Uncertainty due to bias-correction is found to have greatest influence on projections of extreme river flows, and the choice of method(s) is an important consideration in snowmelt systems. Overall, hydrological model parameterization is least important. The study also demonstrates how an improved understanding of the physical processes governing future river flows can help focus attention on the scientifically tractable elements of the uncertainty.

Soil moisture and evapotranspiration of different land cover types in the Loess Plateau, China

Abstract: We studied the impacts of re-vegetation on soil moisture dynamics and evapotranspiration (ET) of five land cover types in the Loess Plateau in northern China. Soil moisture and temperature variations under grass ( Andropogon ), subshrub ( Artemisia scoparia ), shrub ( Spiraea pubescens ), plantation forest ( Robinia pseudoacacia ), and crop ( Zea mays ) vegetation were continuously monitored during the growing season of 2011. There were more than 10 soil moisture pulses during the period of data collection. Surface soil moisture of all of the land cover types showed an increasing trend in the rainy season. Soil moisture under the corn crop was consistently higher than the other surfaces. Grass and subshrubs showed an intermediate moisture level. Grass had slightly higher readings than those of subshrub most of the time. Shrubs and plantation forests were characterized by lower soil moisture readings, with the shrub levels consistently being slightly higher than those of the forests. Despite the greater post-rainfall loss of moisture under subshrub and grass vegetation than forests and shrubs, subshrub and grass sites exhibit a higher soil moisture content due to their greater soil retention capacity in the dry period. The daily ET trends of the forests and shrub sites were similar and were more stable than those of the other types. Soils under subshrubs acquired and retained soil moisture resources more efficiently than the other cover types, with a competitive advantage in the long term, representing an adaptive vegetation type in the study watershed. The interactions between vegetation and soil moisture dynamics contribute to structure and function of the ecosystems studied.

Multimodel evaluation of twenty lumped hydrological models under contrasted climate conditions

Abstract: This paper investigates the temporal transposability of hydrological models under contrasted climate conditions and evaluates the added value of using an ensemble of model structures for flow simulation. This is achieved by applying the Differential Split Sample Test procedure to twenty lumped conceptual models on a catchment in the Province of Quebec (Canada) and another one in the State of Bavaria (Germany). First, a calibration/validation procedure was applied on four historical non-continuous periods with contrasted climate conditions. Then, model efficiency was quantified individually (for each model) and collectively (for the model ensemble). The individual analysis evaluated model performance and robustness. The ensemble investigation, based on the average of simulated discharges, focused on the twenty-member ensemble and all possible model subsets. Results showed that using a single model may provide hazardous results when the model is to be applied in contrasted conditions. Overall, some models turned out as a good compromise in terms of performance and robustness, but generally not as much as the twenty-model ensemble. Model subsets offered yet improved performance over the twenty-model ensemble, but at the expanse of spatial transposability (i.e. need of site-specific analysis).

Towards an integrated soil moisture drought monitor for East Africa

Abstract: Drought in East Africa is a recurring phenomenon with significant humanitarian impacts. Given the steep climatic gradients, topographic contrasts, general data scarcity, and, in places, political instability that characterize the region, there is a need for spatially distributed, remotely derived monitoring systems to inform national and international drought response. At the same time, the very diversity and data scarcity that necessitate remote monitoring also make it difficult to evaluate the reliability of these systems. Here we apply a suite of remote monitoring techniques to characterize the temporal and spatial evolution of the 2010–2011 Horn of Africa drought. Diverse satellite observations allow for evaluation of meteorological, agricultural, and hydrological aspects of drought, each of which is of interest to different stakeholders. Focusing on soil moisture, we apply triple collocation analysis (TCA) to three independent methods for estimating soil moisture anomalies to characterize relative error between products and to provide a basis for objective data merging. The three soil moisture methods evaluated include microwave remote sensing using the Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) sensor, thermal remote sensing using the Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance algorithm, and physically based land surface modeling using the Noah land surface model. It was found that the three soil moisture monitoring methods yield similar drought anomaly estimates in areas characterized by extremely low or by moderate vegetation cover, particularly during the below-average 2011 long rainy season. Systematic discrepancies were found, however, in regions of moderately low vegetation cover and high vegetation cover, especially during the failed 2010 short rains. The merged, TCA-weighted soil moisture composite product takes advantage of the relative strengths of each method, as judged by the consistency of anomaly estimates across independent methods. This approach holds potential as a remote soil moisture-based drought monitoring system that is robust across the diverse climatic and ecological zones of East Africa.

Filling the white space on maps of European runoff trends: estimates from a multi-model ensemble

Abstract: An overall appraisal of runoff changes at the European scale has been hindered by "white space" on maps of observed trends due to a paucity of readily-available streamflow data. This study tested whether this white space can be filled using estimates of trends derived from model simulations of European runoff. The simulations stem from an ensemble of eight global hydrological models that were forced with the same climate input for the period 1963–2000. The derived trends were validated for 293 grid cells across the European domain with observation-based trend estimates. The ensemble mean overall provided the best representation of trends in the observations. Maps of trends in annual runoff based on the ensemble mean demonstrated a pronounced continental dipole pattern of positive trends in western and northern Europe and negative trends in southern and parts of eastern Europe, which has not previously been demonstrated and discussed in comparable detail. Overall, positive trends in annual streamflow appear to reflect the marked wetting trends of the winter months, whereas negative annual trends result primarily from a widespread decrease in streamflow in spring and summer months, consistent with a decrease in summer low flow in large parts of Europe. High flow appears to have increased in rain-dominated hydrological regimes, whereas an inconsistent or decreasing signal was found in snow-dominated regimes. The different models agreed on the predominant continental-scale pattern of trends, but in some areas disagreed on the magnitude and even the direction of trends, particularly in transition zones between regions with increasing and decreasing runoff trends, in complex terrain with a high spatial variability, and in snow-dominated regimes. Model estimates appeared most reliable in reproducing observed trends in annual runoff, winter runoff, and 7-day high flow. Modelled trends in runoff during the summer months, spring (for snow influenced regions) and autumn, and trends in summer low flow were more variable – both among models and in the spatial patterns of agreement between models and the observations. The use of models to display changes in these hydrological characteristics should therefore be viewed with caution due to higher uncertainty.

Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia

Abstract: . The accuracy of three satellite rainfall products (TMPA 3B42RT, CMORPH and PERSIANN) was investigated through comparison with grid cell average ground station rainfall data in Indonesia, with a focus on their ability to detect patterns of low rainfall that may lead to drought conditions. Each of the three products underestimated rainfall in dry season months. The CMORPH and PERSIANN data differed most from ground station data and were also very different from the TMPA 3B42RT data. It proved possible to improve TMPA 3B42RT estimates by applying a single empirical bias correction equation that was uniform in space and time. For the six regions investigated, this reduced the root mean square error for estimates of dry season rainfall totals by a mean 9% (from 44 to 40 mm) and for annual totals by 14% (from 77 to 66 mm). The resulting errors represent 10% and 3% of mean dry season and annual rainfall, respectively. The accuracy of these bias corrected TMPA 3B42RT data is considered adequate for use in real-time drought monitoring in Indonesia. Compared to drought monitoring with only ground stations, this use of satellite-based rainfall estimates offers important advantages in terms of accuracy, spatial coverage, timeliness and cost efficiency.

Coupled daily streamflow and water temperature modelling in large river basins

Abstract: Realistic estimates of daily streamflow and water temperature are required for effective management of water resources (e.g. for electricity and drinking water production) and freshwater ecosystems. Although hydrological and process-based water temperature modelling approaches have been successfully applied to small catchments and short time periods, much less work has been done at large spatial and temporal scales. We present a physically based modelling framework for daily river discharge and water temperature simulations applicable to large river systems on a global scale. Model performance was tested globally at 1/2 × 1/2° spatial resolution and a daily time step for the period 1971–2000. We made specific evaluations on large river basins situated in different hydro-climatic zones and characterized by different anthropogenic impacts. Effects of anthropogenic heat discharges on simulated water temperatures were incorporated by using global gridded thermoelectric water use datasets and representing thermal discharges as point sources into the heat advection equation. This resulted in a significant increase in the quality of the water temperature simulations for thermally polluted basins (Rhine, Meuse, Danube and Mississippi). Due to large reservoirs in the Columbia which affect streamflow and thermal regimes, a reservoir routing model was used. This resulted in a significant improvement in the performance of the river discharge and water temperature modelling. Overall, realistic estimates were obtained at daily time step for both river discharge (median normalized BIAS = 0.3; normalized RMSE = 1.2; r = 0.76) and water temperature (median BIAS = −0.3 °C; RMSE = 2.8 °C; r = 0.91) for the entire validation period, with similar performance during warm, dry periods. Simulated water temperatures are sensitive to headwater temperature, depending on resolution and flow velocity. A high sensitivity of water temperature to river discharge (thermal capacity) was found during warm, dry conditions. The modelling approach has potential to be used for risk analyses and studying impacts of climate change and other anthropogenic effects (e.g. thermal pollution, dams and reservoir regulation) on large rivers.

Hydrological response of a small catchment burned by experimental fire

Abstract: . Fire can considerably change hydrological processes, increasing the risk of extreme flooding and erosion events. Although hydrological processes are largely affected by scale, catchment-scale studies on the hydrological impact of fire in Europe are scarce, and nested approaches are rarely used. We performed a catchment-scale experimental fire to improve insight into the drivers of fire impact on hydrology. In north-central Portugal, rainfall, canopy interception, streamflow and soil moisture were monitored in small shrub-covered paired catchments pre- and post-fire. The shrub cover was medium dense to dense (44 to 84%) and pre-fire canopy interception was on average 48.7% of total rainfall. Fire increased streamflow volumes 1.6 times more than predicted, resulting in increased runoff coefficients and changed rainfall-streamflow relationships – although the increase in streamflow per unit rainfall was only significant at the subcatchment-scale. Fire also fastened the response of topsoil moisture to rainfall from 2.7 to 2.1 h (p = 0.058), and caused more rapid drying of topsoils after rain events. Since soil physical changes due to fire were not apparent, we suggest that changes resulting from vegetation removal played an important role in increasing streamflow after fire. Results stress that fire impact on hydrology is largely affected by scale, highlight the hydrological impact of fire on small scales, and emphasize the risk of overestimating fire impact when upscaling plot-scale studies to the catchment-scale. Finally, they increase understanding of the processes contributing to post-fire flooding and erosion events.