Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models

This is the published version. Copyright 2014 American Geophysical UnionThis paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA uses derivative-based “local” methods to obtain the distribution of parameter sensitivity across the parameter space, which promotes consideration of sensitivity analysis results in the context of simulated dynamics. This work presents DELSA, discusses how it relates to existing methods, and uses two hydrologic test cases to compare its performance with the popular global, variance-based Sobol' method. The first test case is a simple nonlinear reservoir model with two parameters. The second test case involves five alternative “bucket-style” hydrologic models with up to 14 parameters applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both examples, Sobol' and DELSA identify similar important and unimportant parameters, with DELSA enabling more detailed insight at much lower computational cost. For example, in the real-world problem the time delay in runoff is the most important parameter in all models, but DELSA shows that for about 20% of parameter sets it is not important at all and alternative mechanisms and parameters dominate. Moreover, the time delay was identified as important in regions producing poor model fits, whereas other parameters were identified as more important in regions of the parameter space producing better model fits. The ability to understand how parameter importance varies through parameter space is critical to inform decisions about, for example, additional data collection and model development. The ability to perform such analyses with modest computational requirements provides exciting opportunities to evaluate complicated models as well as many alternative models

Improving global hydrological simulations through bias-correction and multi-model blending

There is an immediate need to develop accurate and reliable global hydrological forecasts in light of the future vulnerability to hydrological hazards and water scarcity under a changing climate. As a part of the World Meteorological Organization's (WMO) Global Hydrological Status and Outlook System (HydroSOS) initiative, we investigated different approaches to blending multi-model simulations for developing holistic operational global forecasts. The ULYSSES (mULti-model hYdrological SeaSonal prEdictionS system) dataset, to be published as “Global seasonal forecasts and reforecasts of river discharge and related hydrological variables ensemble from four state-of-the-art land surface and hydrological models” is used in this study. The first step for improving these forecasts is to investigate ways to improve the model simulations, as global models are not calibrated for local conditions. The analysis was performed over 119 different catchments worldwide for the baseline period of 1981–2019 for three variables: evapotranspiration, surface soil moisture and streamflow. This study evaluated blending approaches with a performance metric based (weighted) averaging of the multi-model simulations, using the catchment's Kling-Gupta Efficiency (KGE) for the variable to define the weight. Hydrological model simulations were also bias-corrected to improve the multi-model blending output. Weighted blending in conjunction with bias-correction provided the best improvement in performance for the catchments investigated. Applying modelled weights during blending original simulations improved performance over ungauged catchments. The results indicate that there is potential to successfully and easily implement the bias-corrected weighted blending approach to improve operational forecasts globally. This work can be used to improve water resources management and hydrological hazard mitigation, especially in data-sparse regions

Operational aspects of asynchronous filtering for flood forecasting

This study investigates the suitability of the asynchronous ensemble Kalman filter (AEnKF) and a partitioned updating scheme for hydrological forecasting. The AEnKF requires forward integration of the model for the analysis and enables assimilation of current and past observations simultaneously at a single analysis step. The results of discharge assimilation into a grid-based hydrological model (using a soil moisture error model) for the Upper Ourthe catchment in the Belgian Ardennes show that including past predictions and observations in the data assimilation method improves the model forecasts. Additionally, we show that elimination of the strongly non-linear relation between the soil moisture storage and assimilated discharge observations from the model update becomes beneficial for improved operational forecasting, which is evaluated using several validation measures

Assimilation of Streamflow Observations

Streamflow is arguably the most important predictor in operational hydrologic forecasting and water resources management. Assimilation of streamflow obser- vations into hydrologic models has received growing attention in recent decades as a cost-effective means to improve prediction accuracy. Whereas the methods used for streamflow data assimilation (DA) originated and were popularized in atmospheric and ocean sciences, the nature of streamflow DA is significantly different from that of atmospheric or oceanic DA. Compared to the atmospheric processes modeled in weather forecasting, the hydrologic processes for surface and groundwater flow operate over a much wider range of time scales. Also, most hydrologic systems are severely under-observed. The purpose of this chapter is to provide a review on streamflow measurements and associated uncertainty and to share the latest advances, experiences gained, and science issues and challenges in streamflow DA. Toward this end, we discuss the following aspects of streamflow observations and assimilation methods: (1) measurement methods and uncertainty of streamflow observations, (2) streamflow assimilation applica- tions, and (3) benefits and challenges streamflow DA with regard to large-scale DA, multi-data assimilation, and dealing with timing errors

Generating spatial precipitation ensembles: impact of temporal correlation structure

Sound spatially distributed rainfall fields including a proper spatial and temporal error structure are of key interest for hydrologists to force hydrological models and to identify uncertainties in the simulated and forecasted catchment response. The current paper presents a temporally coherent error identification method based on time-dependent multivariate spatial conditional simulations, which are conditioned on preceding simulations. A sensitivity analysis and real-world experiment are carried out within the hilly region of the Belgian Ardennes. Precipitation fields are simulated for pixels of 10 km × 10 km resolution. Uncertainty analyses in the simulated fields focus on (1) the number of previous simulation hours on which the new simulation is conditioned, (2) the advection speed of the rainfall event, (3) the size of the catchment considered, and (4) the rain gauge density within the catchment. The results for a sensitivity analysis show for typical advection speeds >20 km h<sup>−1</sup>, no uncertainty is added in terms of across ensemble spread when conditioned on more than one or two previous hourly simulations. However, for the real-world experiment, additional uncertainty can still be added when conditioning on a larger number of previous simulations. This is because for actual precipitation fields, the dynamics exhibit a larger spatial and temporal variability. Moreover, by thinning the observation network with 50%, the added uncertainty increases only slightly and the cross-validation shows that the simulations at the unobserved locations are unbiased. Finally, the first-order autocorrelation coefficients show clear temporal coherence in the time series of the areal precipitation using the time-dependent multivariate conditional simulations, which was not the case using the time-independent univariate conditional simulations. The presented work can be easily implemented within a hydrological calibration and data assimilation framework and can be used as an improvement over currently used simplistic approaches to perturb the interpolated point or spatially distributed precipitation estimates

ACID RAIN - A PROBLEM OF THE PRESENT

Kisele kiše postaju jedan od najvažnijih problema čovjekova okoliša, a rezultat su onečišćenosti atmosfere nastale zbog bržeg industrijskog razvoja. Uzroci su oslobađanje oksida sumpora i dušika, koji uz određene kemijske reakcije prelaze u sulfate i nitrate, te mokrim ili suhim taloženjem dolaze do tla. Djeluju na jezera, rijeke, cijeli životinjski i biljni pokrov, uključujući i sva dobra stvorena ljudskom rukom. U dužem razdoblju kisele kiše mogu uništiti organizme koji žive u vodi nekih slatkovodnih ekosustava, ovisno o lokalnim geološkim značajkama (prisutnost prirodnih neutralizatora kiselina u tlu) koje neko područje čine više ili manje osjetljivim na kiselost. Istraživači su utvrdili da je djelovanje H+ na organizme koji žive u vodi različito ovisno o vrstama i koncentracijama kiselosti. Za mnoge vrste problemi započinju već kod pH ≤ 6, a samo nekoliko otpornih vrsta preživljava kod pH ≤ 4,7. Kiselost mijenja kemijski i biokemijski sastav tkiva, smanjuje osmoregulaciju, utječe na razinu hormona u krvi, djeluje na smoltifikaciju riba, te prekida njihovu reprodukciju. Zakiseljavanje osjetljivih vodenih ekosustava u sjevernim dijelovima Zemlje poklapa se s porastom kiselosti oborina. Da ovaj problem ne bi poprimio još šire razmjere, potrebno ga je što hitnije riješiti, bilo kontrolom otpuštanja onečišćivača u atmosferu, bilo sanacijom već nastalih posljedica.Acid rains is one of the most relevant problems of the human environment, the result being pollution of the atmosphere caused by ever growing industrial development. It is caused by the freeing of sulphuric oxides and oxygen, which along with certain chemical reactions transfer into sulphate and nitrate, and through wet or dry sediments reach the ground. This has an effect on lakes, rivers, the entire animal and plant kingdom, including all the good creations of mankind. Over a longer time period acid destroy organisms which live in the water of some freshwater ecosystems, depending on local geological characteristics (presence of natural neutralizers of acid in the ground) which makes an area more of less sensitive to acidity. Investigators have determined that the activity of H+ on organisms which live in the water depend differently on species and concentrations of acidity. For many species the problems begin already with pH ≤ 6, and only a few resistant species survive at pH ≤ 4.7. Acidity changes chemical and biochemical tissue composition, decreases the osmoregulation, influences the level of hormones in the blood, has an effect on fish smoltification, and interrupts its reproduction. Acidifying sensitive water ecosystems in the Northern hemisphere corresponds with the increase of acid precipitation. To prevent this problem from spreading even more it is necessary to solve it as soon as possible, either by controlling the release of pollutants into the atmosphere, or improving of the already occurring consequences

ACID RAIN - A PROBLEM OF THE PRESENT

Kisele kiše postaju jedan od najvažnijih problema čovjekova okoliša, a rezultat su onečišćenosti atmosfere nastale zbog bržeg industrijskog razvoja. Uzroci su oslobađanje oksida sumpora i dušika, koji uz određene kemijske reakcije prelaze u sulfate i nitrate, te mokrim ili suhim taloženjem dolaze do tla. Djeluju na jezera, rijeke, cijeli životinjski i biljni pokrov, uključujući i sva dobra stvorena ljudskom rukom. U dužem razdoblju kisele kiše mogu uništiti organizme koji žive u vodi nekih slatkovodnih ekosustava, ovisno o lokalnim geološkim značajkama (prisutnost prirodnih neutralizatora kiselina u tlu) koje neko područje čine više ili manje osjetljivim na kiselost. Istraživači su utvrdili da je djelovanje H+ na organizme koji žive u vodi različito ovisno o vrstama i koncentracijama kiselosti. Za mnoge vrste problemi započinju već kod pH ≤ 6, a samo nekoliko otpornih vrsta preživljava kod pH ≤ 4,7. Kiselost mijenja kemijski i biokemijski sastav tkiva, smanjuje osmoregulaciju, utječe na razinu hormona u krvi, djeluje na smoltifikaciju riba, te prekida njihovu reprodukciju. Zakiseljavanje osjetljivih vodenih ekosustava u sjevernim dijelovima Zemlje poklapa se s porastom kiselosti oborina. Da ovaj problem ne bi poprimio još šire razmjere, potrebno ga je što hitnije riješiti, bilo kontrolom otpuštanja onečišćivača u atmosferu, bilo sanacijom već nastalih posljedica.Acid rains is one of the most relevant problems of the human environment, the result being pollution of the atmosphere caused by ever growing industrial development. It is caused by the freeing of sulphuric oxides and oxygen, which along with certain chemical reactions transfer into sulphate and nitrate, and through wet or dry sediments reach the ground. This has an effect on lakes, rivers, the entire animal and plant kingdom, including all the good creations of mankind. Over a longer time period acid destroy organisms which live in the water of some freshwater ecosystems, depending on local geological characteristics (presence of natural neutralizers of acid in the ground) which makes an area more of less sensitive to acidity. Investigators have determined that the activity of H+ on organisms which live in the water depend differently on species and concentrations of acidity. For many species the problems begin already with pH ≤ 6, and only a few resistant species survive at pH ≤ 4.7. Acidity changes chemical and biochemical tissue composition, decreases the osmoregulation, influences the level of hormones in the blood, has an effect on fish smoltification, and interrupts its reproduction. Acidifying sensitive water ecosystems in the Northern hemisphere corresponds with the increase of acid precipitation. To prevent this problem from spreading even more it is necessary to solve it as soon as possible, either by controlling the release of pollutants into the atmosphere, or improving of the already occurring consequences