Relevant Hydrological Processes Research Articles

Wflow_sbm v0.7.3, a spatially distributed hydrological model: from global data to local applications

Abstract. The wflow_sbm hydrological model, recently released by Deltares, as part of the Wflow.jl (v0.7.3) modelling framework, is being used to better understand and potentially address multiple operational and water resource planning challenges from a catchment scale to national scale to continental and global scale. Wflow.jl is a free and open-source distributed hydrological modelling framework written in the Julia programming language. The development of wflow_sbm, the model structure, equations and functionalities are described in detail, including example applications of wflow_sbm. The wflow_sbm model aims to strike a balance between low-resolution, low-complexity and high-resolution, high-complexity hydrological models. Most wflow_sbm parameters are based on physical characteristics or processes, and at the same time wflow_sbm has a runtime performance well suited for large-scale high-resolution model applications. Wflow_sbm models can be set a priori for any catchment with the Python tool HydroMT-Wflow based on globally available datasets and through the use of point-scale (pedo)transfer functions and suitable upscaling rules and generally result in a satisfactory (0.4 ≥ Kling–Gupta efficiency (KGE) < 0.7) to good (KGE ≥ 0.7) performance for discharge a priori (without further tuning). Wflow_sbm includes relevant hydrological processes such as glacier and snow processes, evapotranspiration processes, unsaturated zone dynamics, (shallow) groundwater, and surface flow routing including lakes and reservoirs. Further planned developments include improvements on the computational efficiency and flexibility of the routing scheme, implementation of a water demand and allocation module for water resource modelling, the addition of a deep groundwater concept, and computational efficiency improvements through for example distributed computing and graphics processing unit (GPU) acceleration.

A process‐based water stable isotope mixing model for plant water sourcing

AbstractStable isotopes of hydrogen and oxygen in water are common tools for investigating water uptake apportionment, but many of the existing methods rely on simple linear mixing approaches that do not mechanistically incorporate additional information about site physical properties and conditions. Here, we develop a ‘physically based root water uptake isotope mixing estimation’ model (PRIME) that combines a continuous and parametric probability density function for root water uptake with site physical data in a process‐based linear mixing framework. To demonstrate the application of PRIME, water uptake patterns of boreal forest Pinus banksiana trees were estimated on four dates in 2019. To aid in validation, estimates were compared with that of the Bayesian linear mixing model framework, MixSIAR. The two approaches provided similar results, but due to its continuous and parametric nature, PRIME provided estimates of superior resolution, certainty, and model parsimony. Although both models incorporate additional physical information into their mixing frameworks, PRIME does so in a mechanistic manner, thereby reflecting the relevant hydrological processes more effectively than the purely empirical approach taken by MixSIAR. Furthermore, because PRIME uses a continuous function to describe the predicted uptake pattern, it allows users to quantify water uptake with essentially infinite resolution, through integration over the desired depth ranges. These findings demonstrate the advantages of utilizing a continuous, parametric, and process‐based mixing model to estimate root water uptake apportionment, thus providing a relatively simple yet powerful tool with which to approach plant water sourcing.

Challenges in the attribution of river flood events

AbstractAdvances in the field of extreme event attribution allow to estimate how anthropogenic global warming affects the odds of individual climate disasters, such as river floods. Extreme event attribution typically uses precipitation as proxy for flooding. However, hydrological processes and antecedent conditions make the relation between precipitation and floods highly nonlinear. In addition, hydrology acknowledges that changes in floods can be strongly driven by changes in land‐cover and by other human interventions in the hydrological system, such as irrigation and construction of dams. These drivers can either amplify, dampen or outweigh the effect of climate change on local flood occurrence. Neglecting these processes and drivers can lead to incorrect flood attribution. Including flooding explicitly, that is, using data and models of hydrology and hydrodynamics that can represent the relevant hydrological processes, will lead to more robust event attribution, and will account for the role of other drivers beyond climate change. Existing attempts are incomplete. We argue that the existing probabilistic framework for extreme event attribution can be extended to explicitly include floods for near‐natural cases, where flood occurrence was unlikely to be influenced by land‐cover change and human hydrological interventions. However, for the many cases where this assumption is not valid, a multi‐driver framework for conditional event attribution needs to be established. Explicit flood attribution will have to grapple with uncertainties from lack of observations and compounding from the many processes involved. Further, it requires collaboration between climatologists and hydrologists, and promises to better address the needs of flood risk management.This article is categorized under: Paleoclimates and Current Trends > Modern Climate Change Paleoclimates and Current Trends > Detection and Attribution Assessing Impacts of Climate Change > Observed Impacts of Climate Change

CalBMP, a web-based modeling tool for evaluating pesticide offsite movement and best management practice scenarios in California agricultural land

Quantitative evaluation of best management practice (BMP) effectiveness can help stakeholders to make better watershed management decisions. However, such evaluations are always challenging as they require complex algorithms to simulate the relevant hydrological processes, crop growth and the corresponding pollutant transport pathways in order to evaluate potential BMPs and select the best one for the specific field conditions. In this study, a web-based interface (CalBMP) was developed to predict BMP effectiveness in California, focusing on pesticide modeling at the field scale. With built-in databases for soil, weather, crop, pesticides, and BMPs, users can run simulations for baseline and BMP scenarios using their site-specific field conditions by simply providing the field information, such as zip code, soil, crop management, and pesticide application data. CalBMP uses PRZM5 + , a USEPA model, to simulate pesticide transport and fate at the field edge. The CalBMP simulations were validated based on measurements from an alfalfa field study. The results indicated that the CalBMP interface could reasonably simulate the runoff and adsorbed pesticide loss leaving the field with default parameters from previously known field parameters or public databases. CalBMP underestimated sediment erosion, possibly due to uncertainties in field measurements or inaccurate simulation of the temporal distribution of flood irrigation. CalBMP is likely to underestimate pesticides with greater solubility, such as diuron, because PRZM5 + uses the simplified instantaneous equilibrium sorption model. In addition, a strawberry field study was adopted to demonstrate the capability of the CalBMP interface for simulating BMP effectiveness (pesticide reduction percentage in the main pathways) with easy-to-understand graphs and tables. The results indicated that users can easily compare and review the results from multiple scenarios, which could facilitate the decision-making process for mitigating the amount of active ingredient bifenthrin leaving the field. The CalBMP tool provides useful information on pesticide runoff potential and BMP selection at the field scale. With increasingly stringent regulations for water quality protection, CalBMP will add to the growers’ toolbox for minimizing the environmental impacts from their inevitable pesticide usage.

Process-based ecosystem models to support management of drained peatland forests

Forested peatlands are globally significant carbon pools, important forest resources and areas for other bioproduction. Management of drained peatland forests has partly contradictory targets, such as economic profit, climate change mitigation and adaptation, and water protection. Balancing between these targets by comparing different management options requires a thorough understanding of the ecosystem processes, as well as modelling tools that are able to represent their complexity. This thesis presents three such tools, which are based on process-based models, and their applications to concrete water table management scenarios in drained peatlands. All three works are built upon a common peat hydrological model. Two of the studies analyze the effect of canal-blocking restoration practices on the water table and carbon dioxide emissions in tropical peatlands. The first work shows that using optimization algorithms to choose the location of a fixed number of canal blocks can lead to sizeable improvements on the amount of peat they rewet. The second work systematically analyzes the impact of canal blocks on tropical peatland water tables, and provides insights about their performance for different weather conditions and peat types. The third study presents a peatland ecosystem model focused on the effect of drainage on nutrient dynamics and forest growth in boreal peatlands. By connecting the relevant hydrological and biogeochemical processes, this ecosystem model enables the study of interconnected phenomena such as the identification of the stand growth limiting factor, and the impact of typical ditch network management operations on the nutrient balance and forest productivity.

Overcoming equifinality: time-varying analysis of sensitivity and identifiability of SWAT runoff and sediment parameters in an arid and semiarid watershed.

The phenomenon of "equifinality for different parameters" limits the link between parameters and catchment characteristics; however, solving the equifinality problem is a major challenge in the development, generalization, and application of a model. This study focused on the Yanhe River Watershed to investigate the time-varying characteristics of sensitivity and identifiability of SWAT (Soil and Water Assessment Tool) runoff and sediment parameters based on the Sobol' and generalized likelihood uncertainty estimation methods. The results indicate that (i) the nondominated sorting genetic algorithm-II has good adaptability and reliability in parameter calibration of the SWAT model in the Yanhe River Watershed. The evaluation indicators (Nash-Sutcliffe efficiency, R2, and percent bias) of monthly runoff and sediment in the Ganguyi hydrological station were all satisfactory per the SWAT model during the calibration and validation periods. (ii) The interaction between runoff and sediment parameters is a crucial reason for parameter sensitivity, which has obvious time-varying characteristics and is largely dependent on precipitation in the Yanhe River Watershed. Temporal and spatial variability of precipitation should be considered in the detailed analysis of parameter identifiability, and watershed managers should not ignore changes in the runoff process when regulating sediment. (iii) Only a relatively small number of parameters can be identified in the runoff and sediment simulation process of the Yanhe River Watershed, such as CN2 (initial soil conservation service runoff curve number for moisture condition II), CH_K2 (effective hydraulic conductivity in main channel alluvium), ALPHA_BF (baseflow alpha factor), USLE_C (cover and management factor), USLE_P (support practice factor), and USLE_K (soil erodibility factor), due to high surface runoff, reduced lag time, reduced low flows, increased peak flows, and channel erosion, respectively. More importantly, there is a strong positive correlation between parameter identifiability and parameter sensitivity. Both are effective methods of parameter diagnosis, but the identifiability of parameters is not equivalent to its sensitivity. Our results strongly suggest that a detailed parameter sensitivity and identifiability analysis is a critical step in improving hydrological model performance to reduce the risk of "equifinality for different parameters" while articulating all relevant hydrological processes.

Impacts of groundwater flow on the evolution of a thermokarst lake in the permafrost–dominated region on the Qinghai–Tibet plateau

AbstractAs a result of global warming induced permafrost degradation in recent decades, thermokarst lakes in the Qinghai–Tibet plateau (QTP) have been regulating local hydrological and ecological processes. Simulations with coupled moisture–heat numerical models in the Beiluhe basin (located in the hinterland of permafrost regions on the QTP) have provided insights into the interaction between groundwater flow and the freeze–thaw process. A total of 30 modified SUTRA scenarios were established to examine the effects of hydrodynamic forces, permeability, and climate on thermokarst lakes. The results indicate that the hydrodynamic condition variables regulate the permafrost degradation around the lakes. In case groundwater recharges to the lake, a low–temperature groundwater flow stimulates the expansion of the surrounding thawing regions through thermal convection. The thawing rate of the permafrost underlying the lake intensifies when groundwater is discharged from the lake. Under different permeability conditions, spatiotemporal variations in the active layer thickness significantly influence the occurrence of an open talik at the lake bottom. A warmer and wetter climate will inevitably lead to a sharp decrease in the upper limit of the surrounding permafrost, with a continual decrease in the duration of open talik events. Overall, our results underscore that comprehensive consideration of the relevant hydrologic processes is critical for improving the understanding of environmental and ecological changes in cold environments.

Identification of sensitive parameters in daily and monthly hydrological simulations in small to large catchments in Central India

Hydrological models have many parameters representing various hydrological processes. These parameters are effective at different spatial and temporal resolution. Most of the parameters can be measured such as slope, elevation, area, vegetation type etc., but others cannot be estimated from the available data. Thus, they remain unknown in a hydrological simulation. Local and Global Sensitivity Analyses (LSA and GSA respectively) are therefore used to reduce the number of parameters that need to be equipped with input–output data. GSA also improves the efficiency of the model calibration and validation which in turn increases the reliability of the model. In this paper, we investigate into the effect of size of a catchment (small, medium, and large) time steps of simulation (Daily and Monthly), and the choice of GSA method in performing sensitivity analysis. A Soil and Water Assessment Tool (SWAT) hydrologic model is developed for 10 subbasins of Narmada River basin at daily and monthly temporal simulations from January 1991 to December 2000. The sensitivity of 29 input parameters have been analysed with two GSA methods: the multilinear regression SA used by sequential uncertainty fitting algorithm (SUFI-2) in SWAT – Calibration and Uncertainty procedure (SWAT-CUP), and the first order sensitivity indices driven by Fourier Amplitude Sensitivity Test (FAST). Our results show that a hydrological model set up with only sensitive parameters can also produce similar results as when all the parameters are considered. We concluded that the selection of catchment size and simulation time step strongly influence the parameter sensitivity. Our results show that the sensitivity of some of the parameters like Curve number for moisture condition (CN2.mgt), baseflow alpha factor for bank storage (ALPHA_BNK.rte) and lateral flow travel time (LAT_TTIME.hru) are independent of catchment size and simulation time step. Moreover, baseflow alpha factor for the recession constant (ALPHA_BF.gw), manning’s value for overland flow (OV_N.hru) and soil erodibility factor (USLE_K(..).sol) are not sensitive for large and medium range watersheds but those are sensitive for small watershed at a monthly time step. Ground water delay (GW_DELAY.gw), average slope steepness (HRU_SLP.hru) and support practice (p) factor of USLE soil equation (USLE_P.mgt) are not sensitive for large watersheds but sensitive for small and medium range watersheds at a daily time step. Our results strongly recommends that a detailed parameter sensitivity analysis is an important step in setting up any hydrological model to reduce the number of parameters while addressing all relevant hydrological processes.

Sources and variability of CO2 in a prealpine stream gravel bar

AbstractGravel bars (GBs) contribute to carbon dioxide (CO2) emissions from stream corridors, with CO2 concentrations and emissions dependent on prevailing hydraulic, biochemical, and physicochemical conditions. We investigated CO2 concentrations and fluxes across a GB in a prealpine stream over three different discharge‐temperature conditions. By combining field data with a reactive transport groundwater model, we were able to differentiate the most relevant hydrological and biogeochemical processes contributing to CO2 dynamics. GB CO2 concentrations showed significant spatial and temporal variability and were highest under the lowest flow and highest temperature conditions. Further, observed GB surface CO2 evasion fluxes, measured CO2 concentrations, and modelled aerobic respiration were highest at the tail of the GB over all conditions. Modelled CO2 transport via streamwater downwelling contributed the largest fraction of the measured GB CO2 concentrations (31% to 48%). This contribution increased its relative share at higher discharges as a result of a decrease in other sources. Also, it decreased from the GB head to tail across all discharge‐temperature conditions. Aerobic respiration accounted for 17% to 36% of measured surface CO2 concentrations. Zoobenthic respiration was estimated to contribute between 4% and 8%, and direct groundwater CO2 inputs 1% to 23%. Unexplained residuals accounted for 6% to 37% of the observed CO2 concentrations at the GB surface. Overall, we highlight the dynamic role of subsurface aerobic respiration as a driver of spatial and temporal variability of CO2 concentrations and evasion fluxes from a GB. As hydrological regimes in prealpine streams are predicted to change following climatic change, we propose that warming temperatures combined with extended periods of low flow will lead to increased CO2 release via enhanced aerobic respiration in newly exposed GBs in prealpine stream corridors.

Groundwater salinity variation in Upazila Assasuni (southwestern Bangladesh), as steered by surface clay layer thickness, relative elevation and present-day land use

Abstract. In the southwestern coastal region of Bangladesh, options for drinking water are limited by groundwater salinity. To protect and improve the drinking water supply, the large variation in groundwater salinity needs to be better understood. This study identifies the palaeo and present-day hydrological processes and their geographical or geological controls that determine variation in groundwater salinity in Upazila Assasuni in southwestern Bangladesh. Our approach involved three steps: a geological reconstruction, based on the literature; fieldwork to collect high-density hydrological and lithological data; and data processing to link the collected data to the geological reconstruction in order to infer the evolution of the groundwater salinity in the study area. Groundwater freshening and salinization patterns were deduced using PHREEQC cation exchange simulations and isotope data were used to derive relevant hydrological processes and water sources. We found that the factor steering the relative importance of palaeo and present-day hydrogeological conditions was the thickness of the Holocene surface clay layer. The groundwater in aquifers under thick surface clay layers is controlled by the palaeohydrological conditions prevailing when the aquifers were buried. The groundwater in aquifers under thin surface clay layers is affected by present-day processes, which vary depending on present-day surface elevation. Slightly higher-lying areas are recharged by rain and rainfed ponds and therefore have fresh groundwater at shallow depth. In contrast, the lower-lying areas with a thin surface clay layer have brackish–saline groundwater at shallow depth because of flooding by marine-influenced water, subsequent infiltration and salinization. Recently, aquaculture ponds in areas with a thin surface clay layer have increased the salinity in the underlying shallow aquifers. We hypothesize that to understand and predict shallow groundwater salinity variation in southwestern Bangladesh, the relative elevation and land use can be used as a first estimate in areas with a thin surface clay layer, while knowledge of palaeohydrogeological conditions is needed in areas with a thick surface clay layer.

Sulfate variations as a natural tracer for conduit‐matrix interaction in a complex karst aquifer

AbstractLarge areas of Europe, especially in the Alps, are covered by carbonate rocks, and karst springs are an important source for drinking water supply. Because of their high variability and heterogeneity, understanding the hydrogeological functioning is of particular importance for protection of karst aquifers. In this study, hydrogeochemical investigations characterized the water of a spring draining a complex carbonate‐gypsum karst system in the Alps. The reaction of the spring to a rainfall event was examined to identify the relevant hydrological processes controlling the hydrochemistry of the spring, and to understand water‐rock interactions and conduit–matrix exchange. A fast and marked reaction of discharge and electrical conductivity was observed. The main cations are Ca2+ and Mg2+, which showed a distinct decrease after the rainfall. Bicarbonate and sulfate were identified as major anions. Although HCO3− showed only minor fluctuations, SO42− decreased by 72% after the rain event. Comparisons of ion ratios show that both carbonate and gypsum rocks influence the water chemistry of the spring. The rainfall event caused a dilution effect, but dilution alone cannot explain the observed water chemistry. A conceptual model of the spring behaviour during low‐flow and high‐flow conditions, including conduit–matrix interaction, was developed, which can explain the observations. This study aims to give new insights into the highly dynamic exchange processes between karst conduits and the surrounding matrix, and the results demonstrated that (a) during low‐flow conditions, the spring is characterized by high sulfate content, but after rainfall events, the water chemistry is dominated by bicarbonate. These findings show the dependency of water chemistry from the lithology; (b) a change in water chemistry is associated with a significant shift from low‐flow to high‐flow conditions; (c) conduit–matrix exchange is an important factor as shown by the discharge–sulfate relationship and clearly influences the behaviour of the spring.

Influence of moisture source dynamics and weather patterns on stable isotopes ratios of precipitation in Central-Eastern Africa

We report the first δ18O and δ2H data of Virunga rainfall in the Eastern Democratic Republic of the Congo, situated on the limit between Central and Eastern Africa. The dataset is from 13 rain gauges deployed at Mount Nyiragongo and its surroundings sampled monthly between December 2013 and October 2015. The δ18O and δ2H vary from −6.44 to 6.16‰, and −32.53 to 58.89‰ respectively, and allowed us to define a LMWL of δ2H = 7.60δ18O + 16.18. Three main wind directions, i.e. NE, E and SE, were identified in the upper atmosphere corresponding to three major moisture source regions. On the contrary, lower atmospheric winds are weaker in nature and originate mainly from the S and SW, creating a topographically-driven, more local moisture regime. The latter is due to the accumulation in the floor of the rift of water vapor from Lake Kivu forming a layer of isotopically enriched vapor that mediates the isotope enrichment of the falling raindrops. A strong seasonality is observed in both δ18O and δ2H data, and is primarily driven by combined seasonal and spatial variation in the moisture sources. The δ18O and δ2H seasonality is thus correlated to weather patterns, as the latter control the wet to dry season shifting, and vice versa. The key characteristic of seasonality is the variation of monthly precipitation amounts, since the mean monthly air temperature is nearly constant on an annual scale. Two regionally relevant hydrological processes contribute to the isotopic signature: namely moisture uptake from the isotopically enriched surface waters of East African lakes and from the depleted soil-water and plants. Consequently, the proportion of water vapor from each of these reservoirs in the atmosphere drives the enrichment or depletion of δ2H and δ18O in the precipitation. Thus, during wet periods the vapor from soil-plants evapotranspiration dominates yielding isotopically depleted precipitation, contrary to dry periods when vapor from lakes surface evaporation dominates, yielding isotopically enriched precipitation. At the global scale, our dataset reduces gaps in this region that has been poorly studied for δ18O and δ2H in precipitation. At the regional scale, the improved understanding of the ways land cover, moisture source seasonal and spatial dynamics, and atmospheric patterns impact precipitation spatial and temporal variabilities in Central-East African will contribute to the ongoing research on mitigating the impacts of ongoing climate change in Sub-Saharan Africa. The reduction of gaps and uncertainties in δ2H and δ18O of precipitation, and the understanding of their interrelation with weather patterns are essential for a better past, present and future environmental and climatic modelling at both local and regional scales.

PondR: a process-oriented model to simulate the hydrology of drainage ponds

Abstract Drainage ponds are a useful measure to manage water resources. However, these small water bodies are characterized by highly dynamic internal processes. This article discusses a simple process-oriented model developed to simulate temporal dynamics of internal processes within drainage ponds. The PondR model is able to simulate the relevant hydrological processes of the pond by using commonly available input data. For model development, data from a 3-year monitoring campaign of the investigated drainage pond served to validate the newly developed model for the autumn and winter time periods. A temporal parameter sensitivity analysis (TEDPAS) revealed that groundwater parameters are predominant during the whole year. The model performed well in simulating outflow together with simulated pond volume and improved the understanding of the hydrological regime for drainage ponds. Regarding the practical benefit, the developed PondR model could be useful in future studies for more precise planning of pond dimensions and water resource management in the field of research and engineering services.

Assessment of land use land cover change impact on hydrological regime of a basin

The sustainability of water resources mainly depends on planning and management of land use; a small change in it may affect water yield largely, as both are linked through relevant hydrological processes, explicitly. However, human activities, especially a significant increase in population, in-migration and accelerated socio-economic activities, are constantly modifying the land use and land cover (LULC) pattern. The impact of such changes in LULC on the hydrological regime of a basin is of widespread concern and a great challenge to the water resource engineers. While studying these impacts, the issue that prevails is the selection of a hydrological model that may be able to accommodate spatial and temporal dynamics of the basin with higher accuracy. Therefore, in the present study, the capabilities of variable infiltration capacity hydrological model to hydrologically simulate the basin under varying LULC scenarios have been investigated. For the present analysis, the Pennar River Basin, Andhra Pradesh, which falls under a water scarce region in India, has been chosen. The water balance components such as runoff potential, evapotranspiration (ET) and baseflow of Pennar Basin have been simulated under different LULC scenarios to study the impact of change on hydrological regime of a basin. Majorly, increase in built-up (13.94% approx.) and decrease in deciduous forest cover (2.44%) are the significant changes observed in the basin during the last three decades. It was found that the impact of LULC change on hydrology is balancing out at basin scale (considering the entire basin, while routing the runoff at the basin outlet). Therefore, an analysis on spatial variation in each of the water balance components considered in the study was done at grid scale. It was observed that the impact of LULC is considerable spatially at grid level, and the maximum increase of 265 mm (1985–2005) and the decrease of 48 mm (1985–1995) in runoff generation at grid were estimated. On the contrary, ET component showed the maximum increase of 400 and decrease of 570 mm under different LULC change scenario. Similarly, in the base flow parameter, an increase of 70 mm and the decrease of 100 mm were observed. It was noticed that the upper basin is showing an increasing trend in almost all hydrological components as compared to the lower basin. Based on this basin scale study, it was concluded that change in the land cover alters the hydrology; however, it needs to be studied at finer spatial scale rather than the entire basin as a whole. The information like the spatial variation in hydrological components may be very useful for local authority and decision-makers to plan mitigation strategies accordingly.

Process verification of a hydrological model using a temporal parameter sensitivity analysis

Abstract. To ensure reliable results of hydrological models, it is essential that the models reproduce the hydrological process dynamics adequately. Information about simulated process dynamics is provided by looking at the temporal sensitivities of the corresponding model parameters. For this, the temporal dynamics of parameter sensitivity are analysed to identify the simulated hydrological processes. Based on these analyses it can be verified if the simulated hydrological processes match the observed processes of the real world. We present a framework that makes use of processes observed in a study catchment to verify simulated hydrological processes. Temporal dynamics of parameter sensitivity of a hydrological model are interpreted to simulated hydrological processes and compared with observed hydrological processes of the study catchment. The results of the analysis show the appropriate simulation of all relevant hydrological processes in relation to processes observed in the catchment. Thus, we conclude that temporal dynamics of parameter sensitivity are helpful for verifying simulated processes of hydrological models.

Parameter dimensionality reduction of a conceptual model for streamflow prediction in Canadian, snowmelt dominated ungauged basins

This paper evaluated the effects of parametric reduction of a hydrological model on five regionalization methods and 267 catchments in the province of Quebec, Canada. The Sobol’ variance-based sensitivity analysis was used to rank the model parameters by their influence on the model results and sequential parameter fixing was performed. The reduction in parameter correlations improved parameter identifiability, however this improvement was found to be minimal and was not transposed in the regionalization mode. It was shown that 11 of the HSAMI models’ 23 parameters could be fixed with little or no loss in regionalization skill. The main conclusions were that (1) the conceptual lumped models used in this study did not represent physical processes sufficiently well to warrant parameter reduction for physics-based regionalization methods for the Canadian basins examined and (2) catchment descriptors did not adequately represent the relevant hydrological processes, namely snow accumulation and melt.

SPHY v2.0: Spatial Processes in HYdrology

Abstract. This paper introduces and presents the Spatial Processes in HYdrology (SPHY) model (v2.0), its development background, its underlying concepts, and some example applications. SPHY has been developed with the explicit aim of simulating terrestrial hydrology on flexible scales, under various physiographical and hydroclimatic conditions, by integrating key components from existing and well-tested models. SPHY is a spatially distributed leaky bucket type of model, and is applied on a cell-by-cell basis. The model is written in the Python programming language using the PCRaster dynamic modeling framework. SPHY (i) integrates most hydrologic processes, (ii) has the flexibility to be applied in a wide range of hydrologic applications, and (iii) on various scales, and (iv) can easily be implemented. The most relevant hydrological processes that are integrated into the SPHY model are rainfall–runoff processes, cryosphere processes, evapotranspiration processes, the dynamic evolution of vegetation cover, lake/reservoir outflow, and the simulation of root-zone moisture contents. Studies in which the SPHY model was successfully applied and tested are described in this paper, including (i) real-time soil moisture predictions to support irrigation management in lowland areas, (ii) climate change impact studies in snow- and glacier-fed river basins, and (iii) operational flow forecasting in mountainous catchments.

Remote sensing of drought: Progress, challenges and opportunities

AbstractThis review surveys current and emerging drought monitoring approaches using satellite remote sensing observations from climatological and ecosystem perspectives. We argue that satellite observations not currently used for operational drought monitoring, such as near‐surface air relative humidity data from the Atmospheric Infrared Sounder mission, provide opportunities to improve early drought warning. Current and future satellite missions offer opportunities to develop composite and multi‐indicator drought models. While there are immense opportunities, there are major challenges including data continuity, unquantified uncertainty, sensor changes, and community acceptability. One of the major limitations of many of the currently available satellite observations is their short length of record. A number of relevant satellite missions and sensors (e.g., the Gravity Recovery and Climate Experiment) provide only a decade of data, which may not be sufficient to study droughts from a climate perspective. However, they still provide valuable information about relevant hydrologic and ecological processes linked to this natural hazard. Therefore, there is a need for models and algorithms that combine multiple data sets and/or assimilate satellite observations into model simulations to generate long‐term climate data records. Finally, the study identifies a major gap in indicators for describing drought impacts on the carbon and nitrogen cycle, which are fundamental to assessing drought impacts on ecosystems.

Comparing calibrated parameter sets of the SWAT model for the Scandinavian and Iberian peninsulas

Different SWAT models have been set-up to predict water discharge at the European scale, applying an innovative modelling protocol that involves sensitivity analysis, multi-variable calibration and regionalization of the calibrated parameters. In this application, two large regions have been considered: the Scandinavian and the Iberian peninsulas, with the main objectives: (a) to study the spatial variation of calibrated parameter sets obtained for selected sub-basins, and (b) identification of the most relevant hydrological processes in each region. The results of the analysis highlight that snow processes are dominant in Scandinavia; groundwater processes are significant in both the Scandinavian and Iberian peninsulas, while lateral flow is not significant in either region. Calibrated soil hydraulic parameters have different ranges of values in each region, reflecting a difference in runoff-generating mechanisms between the two studied regions. The contribution of this analysis is the assessment of the main differences between hydrological processes across Europe and understanding of the major transport pathways for pollutants.Editor Z.W. Kundzewicz; Guest editor V. Krysanova

Uncertainty in a monthly water balance model using the generalized likelihood uncertainty estimation methodology

Hydrological models are simplified representations of natural processes and subject to errors. Uncertainty bounds are a commonly used way to assess the impact of an input or model architecture uncertainty in model outputs. Different sets of parameters could have equally robust goodness-of-fit indicators, which is known as Equifinality. We assessed the outputs from a lumped conceptual hydrological model to an agricultural watershed in central Chile under strong interannual variability (coefficient of variability of 25%) by using the Equifinality concept and uncertainty bounds. The simulation period ran from January 1999 to December 2006. Equifinality and uncertainty bounds from GLUE methodology (Generalized Likelihood Uncertainty Estimation) were used to identify parameter sets as potential representations of the system. The aim of this paper is to exploit the use of uncertainty bounds to differentiate behavioural parameter sets in a simple hydrological model. Then, we analyze the presence of equifinality in order to improve the identification of relevant hydrological processes. The water balance model for Chillan River exhibits, at a first stage, equifinality. However, it was possible to narrow the range for the parameters and eventually identify a set of parameters representing the behaviour of the watershed (a behavioural model) in agreement with observational and soft data (calculation of areal precipitation over the watershed using an isohyetal map). The mean width of the uncertainty bound around the predicted runoff for the simulation period decreased from 50 to 20 m3s−1 after fixing the parameter controlling the areal precipitation over the watershed. This decrement is equivalent to decreasing the ratio between simulated and observed discharge from 5.2 to 2.5. Despite the criticisms against the GLUE methodology, such as the lack of statistical formality, it is identified as a useful tool assisting the modeller with the identification of critical parameters.