TY - JOUR A1 - Pilz, Tobias A1 - Francke, Till A1 - Baroni, Gabriele A1 - Bronstert, Axel T1 - How to Tailor my process-based hydrological model? BT - dynamic identifiability analysis of flexible model structures JF - Water resources research N2 - In the field of hydrological modeling, many alternative representations of natural processes exist. Choosing specific process formulations when building a hydrological model is therefore associated with a high degree of ambiguity and subjectivity. In addition, the numerical integration of the underlying differential equations and parametrization of model structures influence model performance. Identifiability analysis may provide guidance by constraining the a priori range of alternatives based on observations. In this work, a flexible simulation environment is used to build an ensemble of semidistributed, process-based hydrological model configurations with alternative process representations, numerical integration schemes, and model parametrizations in an integrated manner. The flexible simulation environment is coupled with an approach for dynamic identifiability analysis. The objective is to investigate the applicability of the framework to identify the most adequate model. While an optimal model configuration could not be clearly distinguished, interesting results were obtained when relating model identifiability with hydro-meteorological boundary conditions. For instance, we tested the Penman-Monteith and Shuttleworth & Wallace evapotranspiration models and found that the former performs better under wet and the latter under dry conditions. Parametrization of model structures plays a dominant role as it can compensate for inadequate process representations and poor numerical solvers. Therefore, it was found that numerical solvers of high order of accuracy do often, though not necessarily, lead to better model performance. The proposed coupled framework proved to be a straightforward diagnostic tool for model building and hypotheses testing and shows potential for more in-depth analysis of process implementations and catchment functioning. KW - identifiability analysis KW - flexible model KW - numerics KW - model structure KW - WASA-SED KW - ECHSE Y1 - 2020 U6 - https://doi.org/10.1029/2020WR028042 SN - 0043-1397 SN - 1944-7973 VL - 56 IS - 8 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Reinhardt, Julia A1 - Liersch, Stefan A1 - Abdeladhim, Mohamed Arbi A1 - Diallo, Mori A1 - Dickens, Chris A1 - Fournet, Samuel A1 - Hattermann, Fred A1 - Kabaseke, Clovis A1 - Muhumuza, Moses A1 - Mul, Marloes L. A1 - Pilz, Tobias A1 - Otto, Ilona M. A1 - Walz, Ariane T1 - Systematic evaluation of scenario assessments supporting sustainable integrated natural resources management BT - evidence from four case studies in Africa JF - Ecology and society : a journal of integrative science for resilience and sustainability N2 - Scenarios have become a key tool for supporting sustainability research on regional and global change. In this study we evaluate four regional scenario assessments: first, to explore a number of research challenges related to sustainability science and, second, to contribute to sustainability research in the specific case studies. The four case studies used commonly applied scenario approaches that are (i) a story and simulation approach with stakeholder participation in the Oum Zessar watershed, Tunisia, (ii) a participatory scenario exploration in the Rwenzori region, Uganda, (iii) a model-based prepolicy study in the Inner Niger Delta, Mali, and (iv) a model coupling-based scenario analysis in upper Thukela basin, South Africa. The scenario assessments are evaluated against a set of known challenges in sustainability science, with each challenge represented by two indicators, complemented by a survey carried out on the perception of the scenario assessments within the case study regions. The results show that all types of scenario assessments address many sustainability challenges, but that the more complex ones based on story and simulation and model coupling are the most comprehensive. The study highlights the need to investigate abrupt system changes as well as governmental and political factors as important sources of uncertainty. For an in-depth analysis of these issues, the use of qualitative approaches and an active engagement of local stakeholders are suggested. Studying ecological thresholds for the regional scale is recommended to support research on regional sustainability. The evaluation of the scenario processes and outcomes by local researchers indicates the most transparent scenario assessments as the most useful. Focused, straightforward, yet iterative scenario assessments can be very relevant by contributing information to selected sustainability problems. KW - Africa KW - global and regional change KW - integrated assessments KW - participatory research KW - sustainability science Y1 - 2018 U6 - https://doi.org/10.5751/ES-09728-230105 SN - 1708-3087 VL - 23 IS - 1 PB - Resilience Alliance CY - Wolfville ER - TY - JOUR A1 - Yalew, S. G. A1 - Pilz, Tobias A1 - Schweitzer, C. A1 - Liersch, Stefan A1 - van der Kwast, J. A1 - van Griensven, A. A1 - Mul, Marloes L. A1 - Dickens, Chris A1 - van der Zaag, Pieter T1 - Coupling land-use change and hydrologic models for quantification of catchment ecosystem services JF - Environmental modelling & software with environment data news N2 - Representation of land-use and hydrologic interactions in respective models has traditionally been problematic. The use of static land-use in most hydrologic models or that of the use of simple hydrologic proxies in land-use change models call for more integrated approaches. The objective of this study is to assess whether dynamic feedback between land-use change and hydrology can (1) improve model performances, and/or (2) produce a more realistic quantification of ecosystem services. To test this, we coupled a land-use change model and a hydrologic mode. First, the land-use change and the hydrologic models were separately developed and calibrated. Then, the two models were dynamically coupled to exchange data at yearly time-steps. The approach is applied to a catchment in South Africa. Performance of coupled models when compared to the uncoupled models were marginal, but the coupled models excelled at the quantification of catchment ecosystem services more robustly. KW - Model coupling KW - Ecosystem services KW - Integrated modelling KW - Land and water Y1 - 2018 U6 - https://doi.org/10.1016/j.envsoft.2018.08.029 SN - 1364-8152 SN - 1873-6726 VL - 109 SP - 315 EP - 328 PB - Elsevier CY - Oxford ER - TY - JOUR A1 - Pilz, Tobias A1 - Francke, Till A1 - Bronstert, Axel T1 - lumpR 2.0.0: an R package facilitating landscape discretisation for hillslope-based hydrological models JF - Geoscientific model development : an interactive open access journal of the European Geosciences Union N2 - The characteristics of a landscape pose essential factors for hydrological processes. Therefore, an adequate representation of the landscape of a catchment in hydrological models is vital. However, many of such models exist differing, amongst others, in spatial concept and discretisation. The latter constitutes an essential pre-processing step, for which many different algorithms along with numerous software implementations exist. In that context, existing solutions are often model specific, commercial, or depend on commercial back-end software, and allow only a limited or no workflow automation at all. Consequently, a new package for the scientific software and scripting environment R, called lumpR, was developed. lumpR employs an algorithm for hillslope-based landscape discretisation directed to large-scale application via a hierarchical multi-scale approach. The package addresses existing limitations as it is free and open source, easily extendible to other hydrological models, and the workflow can be fully automated. Moreover, it is user-friendly as the direct coupling to a GIS allows for immediate visual inspection and manual adjustment. Sufficient control is furthermore retained via parameter specification and the option to include expert knowledge. Conversely, completely automatic operation also allows for extensive analysis of aspects related to landscape discretisation. In a case study, the application of the package is presented. A sensitivity analysis of the most important discretisation parameters demonstrates its efficient workflow automation. Considering multiple streamflow metrics, the employed model proved reasonably robust to the discretisation parameters. However, parameters determining the sizes of subbasins and hillslopes proved to be more important than the others, including the number of representative hillslopes, the number of attributes employed for the lumping algorithm, and the number of sub-discretisations of the representative hillslopes. Y1 - 2017 U6 - https://doi.org/10.5194/gmd-10-3001-2017 SN - 1991-959X SN - 1991-9603 VL - 10 SP - 3001 EP - 3023 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Pilz, Tobias A1 - Delgado, José Miguel Martins A1 - Voss, Sebastian A1 - Vormoor, Klaus Josef A1 - Francke, Till A1 - Cunha Costa, Alexandre A1 - Martins, Eduardo A1 - Bronstert, Axel T1 - Seasonal drought prediction for semiarid northeast Brazil BT - what is the added value of a process-based hydrological model? JF - Hydrology and Earth System Sciences N2 - The semiarid northeast of Brazil is one of the most densely populated dryland regions in the world and recurrently affected by severe droughts. Thus, reliable seasonal forecasts of streamflow and reservoir storage are of high value for water managers. Such forecasts can be generated by applying either hydrological models representing underlying processes or statistical relationships exploiting correlations among meteorological and hydrological variables. This work evaluates and compares the performances of seasonal reservoir storage forecasts derived by a process-based hydrological model and a statistical approach. Driven by observations, both models achieve similar simulation accuracies. In a hindcast experiment, however, the accuracy of estimating regional reservoir storages was considerably lower using the process-based hydrological model, whereas the resolution and reliability of drought event predictions were similar by both approaches. Further investigations regarding the deficiencies of the process-based model revealed a significant influence of antecedent wetness conditions and a higher sensitivity of model prediction performance to rainfall forecast quality. Within the scope of this study, the statistical model proved to be the more straightforward approach for predictions of reservoir level and drought events at regionally and monthly aggregated scales. However, for forecasts at finer scales of space and time or for the investigation of underlying processes, the costly initialisation and application of a process-based model can be worthwhile. Furthermore, the application of innovative data products, such as remote sensing data, and operational model correction methods, like data assimilation, may allow for an enhanced exploitation of the advanced capabilities of process-based hydrological models. KW - Water Availability KW - Uncertainty Processor KW - Forecasting Framework KW - Sediment Transport KW - Reservoir Networks KW - Jaguaribe Basin KW - Climate KW - Precipitation KW - Nordeste KW - Connectivity Y1 - 2019 U6 - https://doi.org/10.5194/hess-23-1951-2019 SN - 1027-5606 SN - 1607-7938 VL - 23 SP - 1951 EP - 1971 PB - Copernicus Publications CY - Göttingen ER - TY - JOUR A1 - Pilz, Tobias A1 - Francke, Till A1 - Bronstert, Axel T1 - lumpR 2.0.0: an R package facilitating landscape discretisation for hillslope-based hydrological models JF - Geoscientific model development N2 - The characteristics of a landscape pose essential factors for hydrological processes. Therefore, an adequate representation of the landscape of a catchment in hydrological models is vital. However, many of such models exist differing, amongst others, in spatial concept and discretisation. The latter constitutes an essential pre-processing step, for which many different algorithms along with numerous software implementations exist. In that context, existing solutions are often model specific, commercial, or depend on commercial back-end software, and allow only a limited or no workflow automation at all. Consequently, a new package for the scientific software and scripting environment R, called lumpR, was developed. lumpR employs an algorithm for hillslope-based landscape discretisation directed to large-scale application via a hierarchical multi-scale approach. The package addresses existing limitations as it is free and open source, easily extendible to other hydrological models, and the workflow can be fully automated. Moreover, it is user-friendly as the direct coupling to a GIS allows for immediate visual inspection and manual adjustment. Sufficient control is furthermore retained via parameter specification and the option to include expert knowledge. Conversely, completely automatic operation also allows for extensive analysis of aspects related to landscape discretisation. In a case study, the application of the package is presented. A sensitivity analysis of the most important discretisation parameters demonstrates its efficient workflow automation. Considering multiple streamflow metrics, the employed model proved reasonably robust to the discretisation parameters. However, parameters determining the sizes of subbasins and hillslopes proved to be more important than the others, including the number of representative hillslopes, the number of attributes employed for the lumping algorithm, and the number of sub-discretisations of the representative hillslopes. Y1 - 2017 U6 - https://doi.org/10.5194/gmd-10-3001-2017 SN - 1991-959X SN - 1991-9603 VL - 10 SP - 3001 EP - 3023 PB - Copernicus CY - Göttingen ER -