PCR-GLOBWB 2: a 5 arcmin global hydrological and water resources model

We present PCR-GLOBWB 2, a global hydrology and water resources model. Compared to previous versions of PCR-GLOBWB, this version fully integrates water use. Sector-specific water demand, groundwater and surface water withdrawal, water consumption, and return flows are dynamically calculated at every time step and interact directly with the simulated hydrology. PCR-GLOBWB 2 has been fully rewritten in Python and PCRaster Python and has a modular structure, allowing easier replacement, maintenance, and development of model components. PCR-GLOBWB 2 has been implemented at 5 arcmin resolution, but a version parameterized at 30 arcmin resolution is also available. Both versions are available as open-source codes on https://github.com/UU-Hydro/PCR-GLOBWB_model (Sutanudjaja et al., 2017a). PCR-GLOBWB 2 has its own routines for groundwater dynamics and surface water routing. These relatively simple routines can alternatively be replaced by dynamically coupling PCR-GLOBWB 2 to a global two-layer groundwater model and 1-D–2-D hydrodynamic models. Here, we describe the main components of the model, compare results of the 30 and 5 arcmin versions, and evaluate their model performance using Global Runoff Data Centre discharge data. Results show that model performance of the 5 arcmin version is notably better than that of the 30 arcmin version. Furthermore, we compare simulated time series of total water storage (TWS) of the 5 arcmin model with those observed with GRACE, showing similar negative trends in areas of prevalent groundwater depletion. Also, we find that simulated total water withdrawal matches reasonably well with reported water withdrawal from AQUASTAT, while water withdrawal by source and sector provide mixed results

Hydrograph prediction in ungauged basins: Development of a closure relation for Hortonian runoff

Hydrological forecasting and predictions under environmental change are often hampered by a lack of historical flow measurements and catchment physical data to characterize the system’s behaviour. This thesis presents a parsimonious semi-distributed rainfall-runoff modelling framework based on hydrological response units (HRUs) in which local-scale observable catchment characteristics can be directly used to parameterize the closure relations at the HRU scale. Thus, the modelling framework can potentially be used in ungauged basins where there is no sufficient data for ad-hoc parameter identification (i.e. calibration). The first part of thesis focuses on the development of Hortonian runoff closure relation for HRUs. An extensive data set of rainfall-runoff responses from hypothetical HRUs (6 x105 scenarios), generated from a detailed physically-based hydrological model, is used as a surrogate of real-world data sets to identify the form and parameters of the closure relation. These parameters are, in turn, related to local-scale HRU observables and HRU geometry for each scenario run, resulting in the parameter library to be used for the estimation of closure relation’s parameters for the HRUs outside the synthetic data sets. The closure relations show satisfactory performance in reproducing the observed hydrographs in the 16-km2 catchment in French Alps. Calibration of the closure relation against the observed discharge results in the saturated hydraulic conductivity that is comparable to the values obtained from plot measurements in the study catchment. Thus, the closure relation may be used without calibration if the local-scale observable HRU properties are correctly estimated. The second part of thesis investigates a technique for automated HRU delineation to support a model application at a large scale. This is done using a multiple-point geostatistics (MPS) technique in the context of geomorphological mapping. The MPS technique uses training images to derive the conditional relationships between occurrences of geomorphological types (HRUs) and a set of terrain attributes, consisting of four local morphometric properties and surrounding landforms at two locations. These relations are stored in a frequency database. In the mapping stage, a realization of a geomorphological class is assigned to the target mapping cell based on the probability function of landform class occurrences conditioned to the observed attributes, as retrieved from the frequency database. This technique is tested over 280 km2 in the Buëch catchment, France, using different sizes of training images. The best mapping accuracy (i.e. 51.2% of correct cell, evaluated against the field geomorphological map) can be obtained using training images covering 10% of total area. Small geomorphological features, i.e. hogbacks and glacises, are underrepresented in the automated maps due to sampling bias of these units in the training images. Using these automated geomorphological maps as the HRUs, thus, leads to substantial discharge underestimation, particularly in the dry period where hogbacks are the main runoff-contributing areas. However, this error has small effects for the predictions in the wet period because the catchment runoff is generated from many HRUs. The modelling framework presented in this thesis shows a promise and could serve be as a blueprint for predictions in ungauged basins

Towards closure relations in the Representative Elementary Watershed (REW) framework containing observable parameters: Relations for Hortonian overland flow

This study presents the derivation procedure of an integrated closure relation for infiltration and Hortonian overland flow in the Representative Elementary Watershed (REW) framework that contains directlyobservable parameters. A physically-based high resolution model is used to simulate the infiltration flux and discharge for 6 x 10⁵ set of synthetic REWs and rainstorms scenarios. This synthetic data set serves as a surrogate of real-world data to deduce the closure relation. The closure relation performance is evaluated against the results from the high resolution model. The results show that the closure relation is capable of predicting accurate hydrological responses for an independent set of synthetic REWs and rainstroms in terms of the Nash–Sutcliffe index, errors in total discharge volume, and peak discharge, especially in cases where a relatively large amount of runoff is produced with fast responses. For the estimation of parameters in the closure relation, a local method using inverse distance weighted interpolation in the parameter space is superior to the global method based on the multiple regression, resulting in a better reproduction of runoff characteristics

Towards closure relations in the Representative Elementary Watershed (REW) framework containing observable parameters: Relations for Hortonian overland flow

This study presents the derivation procedure of an integrated closure relation for infiltration and Hortonian overland flow in the Representative Elementary Watershed (REW) framework that contains directlyobservable parameters. A physically-based high resolution model is used to simulate the infiltration flux and discharge for 6 x 10⁵ set of synthetic REWs and rainstorms scenarios. This synthetic data set serves as a surrogate of real-world data to deduce the closure relation. The closure relation performance is evaluated against the results from the high resolution model. The results show that the closure relation is capable of predicting accurate hydrological responses for an independent set of synthetic REWs and rainstroms in terms of the Nash–Sutcliffe index, errors in total discharge volume, and peak discharge, especially in cases where a relatively large amount of runoff is produced with fast responses. For the estimation of parameters in the closure relation, a local method using inverse distance weighted interpolation in the parameter space is superior to the global method based on the multiple regression, resulting in a better reproduction of runoff characteristics

Hortonian runoff closure relations for geomorphologic response units: evaluation against field data

This paper presents an evaluation of the closure relation for Hortonian runoff, proposed in Vannametee et al. (2012), that incorporates a scaling component to explicitly account for the process heterogeneity and scale effects in runoff generation for the real-world case studies. We applied the closure relation, which was embedded in an eventbased lumped rainfall–runoff model, to a 15 km2 catchment in the French Alps. The catchment was disaggregated into a number of landform units, referred to as Geomorphologic Response Units (GRUs), to each of which the closure relation was applied. The scaling component in the closure relation was identified using the empirical relations between rainstorm characteristics, geometry, and local-scale measurable properties of the GRUs. Evaluation of the closure relation performance against the observed discharge shows that the hydrograph and discharge volume were quite satisfactorily simulated even without calibration. Performance of the closure relation can be mainly attributed to the use of scaling component, as it is shown that our closure relation outperforms a benchmark closure relation that lacks this scaling component. The discharge prediction is significantly improved when the closure relation is calibrated against the observed discharge, resulting in local-scale GRUproperties optimal for the predictions. Calibration was done by changing one local-scale observable, i.e. hydraulic conductivity (Ks), using a single pre-factor for the entire catchment. It is shown that the calibrated Ks values are somewhat comparable to the observed Ks values at a local scale in the study catchment. These results suggest that, in the absence of discharge observations, reasonable estimates of catchment-scale runoff responses can possibly be achieved with the observations at the sub-GRU (i.e. plot) scale. Our study provides a platform for the future development of lowdimensional, semi-distributed, physically based discharge models in ungauged catchments

Automated geomorphological mapping using Multiple Point Geostatistics

The geomorphological map is an important tool for studying land-surface processes. Automated mapping ensures a consistent mapping scheme with a reduced field survey time..

Automated geomorphological mapping using Multiple Point Geostatistics

The geomorphological map is an important tool for studying land-surface processes. Automated mapping ensures a consistent mapping scheme with a reduced field survey time..

Development of a transient, lumped hydrologic model for geomorphologic units in a geomorphology based rainfall-runoff modelling framework

We propose a modelling framework for distributed hydrological modelling of 103-105 km2 catchments by discretizing the catchment in geomorphologic units. Each of these units is modelled using a lumped model representative for the processes in the unit. Here, we focus on the development and parameterization of this lumped model as a component of our framework. The development of the lumped model requires rainfall-runoff data for an extensive set of geomorphological units. Because such large observational data sets do not exist, we create artificial data. With a high-resolution, physically-based, rainfall-runoff model, we create artificial rainfall events and resulting hydrographs for an extensive set of different geomorphological units. This data set is used to identify the lumped model of geomorphologic units. The advantage of this approach is that it results in a lumped model with a physical basis, with representative parameters that can be derived from point-scale measurable physical parameters. The approach starts with the development of the high-resolution rainfall-runoff model that generates an artificial discharge dataset from rainfall inputs as a surrogate of a real-world dataset. The model is run for approximately 105 scenarios that describe different characteristics of rainfall, properties of the geomorphologic units (i.e. slope gradient, unit length and regolith properties), antecedent moisture conditions and flow patterns. For each scenario-run, the results of the high-resolution model (i.e. runoff and state variables) at selected simulation time steps are stored in a database. The second step is to develop the lumped model of a geomorphological unit. This forward model consists of a set of simple equations that calculate Hortonian runoff and state variables of the geomorphologic unit over time. The lumped model contains only three parameters: a ponding factor, a linear reservoir parameter, and a lag time. The model is capable of giving an appropriate representation of the transient rainfall-runoff relations that exist in the artificial data set generated with the high-resolution model. The third step is to find the values of empirical parameters in the lumped forward model using the artificial dataset. For each scenario of the high-resolution model run, a set of lumped model parameters is determined with a fitting method using the corresponding time series of state variables and outputs retrieved from the database. Thus, the parameters in the lumped model can be estimated by using the artificial data set. The fourth step is to develop an approach to assign lumped model parameters based upon the properties of the geomorphological unit. This is done by finding relationships between the measurable physical properties of geomorphologic units (i.e. slope gradient, unit length, and regolith properties) and the lumped forward model parameters using multiple regression techniques. In this way, a set of lumped forward model parameters can be estimated as a function of morphology and physical properties of the geomorphologic units. The lumped forward model can then be applied to different geomorphologic units. Finally, the performance of the lumped forward model is evaluated; the outputs of the lumped forward model are compared with the results of the high-resolution model. Our results show that the lumped forward model gives the best estimates of total discharge volumes and peak discharges when rain intensities are not significantly larger than the infiltration capacities of the units and when the units are small with a flat gradient. Hydrograph shapes are fairly well reproduced for most cases except for flat and elongated units with large runoff volumes. The results of this study provide a first step towards developing low-dimensional models for large ungauged basins