Potential Post-Fire Impacts on a Water Supply Reservoir: An Integrated Watershed-Reservoir Approach

Wildfires are an increasing threat in the Mediterranean region, causing frequent losses of goods and human lives. Not only are wildfires a concern due to their immediate effects on vegetation and soil, but they can also have substantial impacts on surface water quality. Approximately one-third of the world’s largest cities obtain their drinking water from forest catchments. The removal of vegetation and consequent runoff increase with a high concentration of ash and sediment often leads to increased nutrient and contaminant loads to downstream reservoirs, damaging the aquatic ecosystem and threatening human health. This study focused on the post-fire degradation of surface water in Castelo de Bode reservoir, a strategic freshwater supply for Lisbon’s metropolitan area (2,000,000 inhabitants), Portugal. Output data from the catchment model Soil and Water Assessment Tool were used as inputs to the CE-QUAL-W2 reservoir model. CE-QUAL-W2 was then calibrated for water level, temperature, nutrients, total suspended solids, chlorophyll-a, and dissolved oxygen. The post-fire impacts were assessed by adjusting land use features (curve number, crop vegetation management factor), and soil properties (soil erodibility) in the catchment model, considering the different impacts of fire (low, medium, and high severity). The reservoir model was able to perform temperature seasonality and stratification while a weak performance was found for chlorophyll-a probably for having considered only a group of algae. Simulations showed a deterioration of water quality at the dam wall during the first year after the forest fire. Nevertheless, contamination did not appear worrisome with regards to water quality standards likely due to the capability of the reservoir to attenuate inflow concentrations.

On the relationship between the variability of catchment hydroclimate and physiography, and the uncertainty of runoff generation hypotheses

<p>Question #20 of the UPH aspires to disentangle and reduce model prediction uncertainty. One feasible approach is to first formulate the relationship between variability (of real-world hydrological processes and catchment characteristics) and uncertainty (of model components and variables), which links the UPH theme of “modelling methods” to “time variability and change” and “space variability and scaling”. Building on this premise, we explored the relationship between runoff generation hypotheses, derived from a large ensemble of catchment model simulations, and catchment characteristics (physiographic, climatic, and streamflow response characteristics) across a large sample of 221 Australian catchments. Using ensembles of 10<sup>6 </sup>runs of SIMHYD model for each catchment, runoff generation hypotheses were formulated based on the interaction of 3 runoff generating fluxes of SIMHYD, namely intensity-based, wetness-based, and slow responses. The hypotheses were derived from model runs with acceptable performance and sufficient parameter sampling. For model performance acceptability, we benchmarked Kling-Gupta Efficiency (KGE) skill score against the calendar day average observed flow, a catchment-specific and more informative benchmark than the conventional observed flow mean. The relative parameter sampling sufficiency was also defined based on the comparative efficacy of two common model parameterisation routines of Latin Hypercube Sampling and Shuffled Complex Evolution for each catchment. Across 186 catchments with acceptable catchment models, we examined the association of uncertain runoff generation hypotheses (i.e. ensemble of modeled runoff fluxes) with 22 catchment attributes. We used the Flux Mapping method (https://doi.org/10.1029/2018WR023750) to characterise the uncertainty of runoff generation hypotheses, and a range of daily and annual summary statistics to characterise catchment attributes. Among the metrics used, Spearman rank correlation coefficient (R<sub>s</sub>) was the most informative metric to capture the functional connectivity of catchment attributes with the internal dynamics of model runoff fluxes, compared to linear Pearson correlation and distance correlation coefficients. We found that streamflow characteristics generally have the most important influence on runoff generation hypotheses, followed by climate and then physiographic attributes. Particularly, daily flow coefficient of variability (Qcv) and skewness (Q Skewness), followed by the same summary statistics of precipitation (Pcv and P Skewness), were most important. These four attributes are strongly correlated with one another, and represent the dynamics of the rainfall-runoff signal within a catchment system. A higher Pcv denotes a higher day-to-day variability in rainfall on the catchment, responded by a higher Qcv flow response. A higher variability in rainfall propagates through the catchment model and translates into a higher degree of equifinality in model runoff fluxes, which implies larger uncertainties of runoff generation hypotheses at catchment scale, and hence a greater challenge for reliable/realistic simulation and prediction of streamflow.</p>

Evaluating Catchment Models as Multiple Working Hypotheses under Uncertainty

Catchment models are conventionally evaluated in terms of their response surface or likelihood surface constructed from model runs using different sets of model parameters. Model evaluation methods are mainly based upon the concept of the equifinality of model structures or parameter sets. The operational definition of equifinality is that multiple model structures/parameters are equally capable of producing acceptable simulations of catchment processes such as runoff. Examining various aspects of this convention, in this thesis I demonstrate their shortcomings and introduce improvements including new approaches and insights for evaluating catchment models as multiple working hypotheses (MWH). First (Chapter 2), arguing that there is more to equifinality than just model structures/parameters, I propose a theoretical framework to conceptualise various facets of equifinality, based on a meta-synthesis of a broad range of literature across geosciences, system theory, and philosophy of science. I distinguish between process-equifinality (equifinality within the real-world systems/processes) and model-equifinality (equifinality within models of real-world systems), explain various aspects of each of these two facets, and discuss their implications for hypothesis testing and modelling of hydrological systems under uncertainty. Second (Chapter 3), building up on this theoretical framework, I propose that characterising model-equifinality based on model internal fluxes — instead of model parameters which is the current approach to account for model-equifinality — provides valuable insights for evaluating catchment models. I developed a new method for model evaluation — called flux mapping — based on the equifinality of runoff generating fluxes of large ensembles of catchment model simulations (1 million model runs for each catchment). Evaluating the model behaviour within the flux space is a powerful approach, beyond the convention, to formulate testable hypotheses for runoff generation processes at the catchment scale. Third (Chapter 4), I further explore the dependency of the flux map of a catchment model upon the choice of model structure and parameterisation, error metric, and data information content. I compare two catchment models (SIMHYD and SACRAMENTO) across 221 Australian catchments (known as Hydrologic Reference Stations, HRS) using multiple error metrics. I particularly demonstrate the fundamental shortcomings of two widely used error metrics — i.e. Nash–Sutcliffe efficiency and Willmott’s refined index of agreement — in model evaluation. I develop the skill score version of Kling–Gupta efficiency (KGEss), and argue it is a more reliable error metric that the other metrics. I also compare two strategies of random sampling (Latin Hypercube Sampling) and guided search (Shuffled Complex Evolution) for model parameterisation, and discuss their implications in evaluating catchment models as MWH. Finally (Chapter 5), I explore how catchment characteristics (physiographic, climatic, and streamflow response characteristics) control the flux map of catchment models (i.e. runoff generation hypotheses). To this end, I formulate runoff generating hypotheses from a large ensemble of SIMHYD simulations (1 million model runs in each catchment). These hypotheses are based on the internal runoff fluxes of SIMHYD — namely infiltration excess overland flow, interflow and saturation excess overland flow, and baseflow — which represent runoff generation at catchment scale. I examine the dependency of these hypotheses on 22 different catchment attributes across 186 of the HRS catchments with acceptable model performance and sufficient parameter sampling. The model performance of each simulation is evaluated using KGEss metric benchmarked against the catchment-specific calendar day average observed flow model, which is more informative than the conventional benchmark of average overall observed flow. I identify catchment attributes that control the degree of equifinality of model runoff fluxes. Higher degree of flux equifinality implies larger uncertainties associated with the representation of runoff processes at catchment scale, and hence pose a greater challenge for reliable and realistic simulation and prediction of streamflow. The findings of this chapter provides insights into the functional connectivity of catchment attributes and the internal dynamics of model runoff fluxes.

Improved Model Parameter Transferability Method for Hydrological Simulation with SWAT in Ungauged Mountainous Catchments

The sustainability of water resources in mountainous areas has a significant contribution to the stabilization and persistence of the ecological and agriculture systems in arid and semi-arid areas. However, the insufficient understanding of hydrological processes in ungauged mountainous catchments (UMCs) is not able to scientifically support the sustainable management of water resources. The conventional parameter transferability method (transplanting the parameters of the donor catchment model with similar distances or attributes to the target catchment model) still has great potential for improving the accuracy of the hydrological simulation in UMC. In this study, 46 river catchments, with discharge survey stations and multi-type catchment characteristics in Xinjiang, are separated into the target catchments and donor catchments to promote an improved model parameter transferability method (IMPTM). This method synthetically processes the SWAT model parameters based on the distance approximation principle (DAP) and the attribute similarity principle (ASP). The performance of this method is tested in a random gauged catchment and compared with other traditional methods (DAP and ASP). The daily runoff simulation results in the target catchment have relatively low accuracy by both the DAP method ( N S = 0.27, R 2 = 0.55) and ASP method ( N S = 0.36, R 2 = 0.65), which implies the conventional approach is not capable of processing the parameters in the target regions. However, the simulation result by IMPTM is a significant improvement ( N S = 0.69, R 2 = 0.85). Moreover, the IMPTM can accurately catch the flow peak, appearance time, and recession curve. The current study provides a compatible method to overcome the difficulties of hydrological simulation in UMCs in the world and can benefit hydrological forecasting and water resource estimation in mountainous areas.

A catchment to coast framework for the evolution of a coastal mangove wetland

<p>Coastal wetlands are at the interface between land and sea, receiving water, sediment and nutrients from upstream catchments and also being subject to tides, wave and changing sea levels. Analysis of their future evolution requires the analysis of the entire catchment to coast system, including the effects of climate variability and change and land use changes. We have developed a modelling framework that is able to include both catchment and coastal processes into the evolution of coastal wetlands by coupling an ecogeomorphological wetland evolution model with a hydrosedimentological catchment model to include both tidal and catchment runoff inputs. We drive the model with storm events and sea-level variations and analyse scenarios of future climate and land use for a catchment in Vanua Levu, Fiji that includes a mangrove wetland at the catchment outlet. We inform our model with field, remote sensing and historical data on land use, tides, sediment and nutrient transport and cyclone activity.</p>

From hillslope to catchment scale hydrologic prediction in a semi-arid region with in-situ observations, satellite soil moisture products, and a distributed catchment model

<p>The water-limited region frequently experiences extreme climate variability.  This region, however, has relatively little hydrological information to characterize the catchment dynamics and its feedback to the climate system. This study assesses the relative benefits of using remotely sensed soil moisture, in addition to sparsely available in-situ soil moisture and stream flow observations, to improve the hydrologic understanding and prediction.  We propose a multi-variable approach to calibrate a hydrologic model, Soil and Water Assessment Tool (SWAT), a semi-distributed, continuous catchment model, with observed streamflow and in-situ soil moisture.  The satellite<span> soil moisture products (~ 5 cm top soil) from the Soil Moisture and Ocean Salinity (SMOS) and the Soil Moisture Active Passive (SMAP) are then used to evaluate the model estimates of soil moisture over the spatial scales through time.  The results show the model calibrated against streamflow only could provide misleading prediction for soil moisture.  Long term in-situ soil moisture observations, albeit limited availability, are crucial to constrain model parameters leading to improved soil moisture prediction at the given site.  </span><span>Satellite soil moisture products </span><span>provide useful information to assess simulated soil moisture results across the spatial domains, filling the gap on the soil moisture information at landscape scales.</span> <span>The preliminary results from this study suggest the potential to produce robust soil moisture and streamflow estimates across scales for a semi-arid region, using a distributed catchment model with in-situ soil network and remotely sensed observations and enhance the overall water budget estimations for multiple hydrologic variables across scales.  </span>This research is conducted on Merriwa catchment, a semi-arid region located in the Upper Hunter Region of NSW, Australia.</p>

Estimation of the Hydraulic Width of the Subcatchment Depending on the Degree of Detail of the Drainage System Model

The article presents the current state of knowledge in the field of estimating preliminary values of storm water subcatchment calibration parameters in the case of using the Storm Water Management Model (SWMM) for building a model of storm water drainage system. The key issue is estimating the runoff width in the case of reducing the network structure and storm water catchments due to the shortening of calculation time and simplification of the model calibration process. Correction of one of the recommended literature methods has been proposed. The assessment was based on the real catchment model with single and multi-family housing. It was found possible to apply the proposed method in the case of reducing systems connected in series.

Comparing SWAT with SWAT-MODFLOW hydrological simulations when assessing the impacts of groundwater abstractions for irrigation and drinking water

Being able to account for temporal patterns of streamflow, the distribution of groundwater resources, as well as the interactions between surface water and groundwater is imperative for informed water resources management. We hypothesize that, when assessing the impacts of water abstractions on streamflow patterns, the benefits of applying a coupled catchment model relative to a lumped semi-distributed catchment model outweigh the costs of additional data requirement and computational resources. We applied the widely used semi-distributed SWAT model and the recently developed SWAT-MODFLOW model, which allows full distribution of the groundwater domain, to a Danish, lowland, groundwater-dominated catchment, the Uggerby River Catchment. We compared the performance of the two models based on the observed streamflow and assessed the simulated streamflow signals of each model when running four groundwater abstraction scenarios with real wells and abstraction rates. The SWAT-MODFLOW model complex was further developed to enable the application of the Drain Package of MODFLOW and to allow auto-irrigation on agricultural fields and pastures. Both models were calibrated and validated, and an approach based on PEST was developed and utilized to enable simultaneous calibration of SWAT and MODFLOW parameters. Both models demonstrated generally good performance for the temporal pattern of streamflow, albeit SWAT-MODFLOW performed somewhat better. In addition, SWAT-MODFLOW generates spatially explicit groundwater-related outputs, such as spatial-temporal patterns of water table elevation. In the abstraction scenarios analysis, both models indicated that abstraction for drinking water caused some degree of streamflow depletion, while abstraction for auto-irrigation led to a slight total flow increase (but a decrease of soil or aquifer water storages, which may influence the hydrology outside the catchment). In general, the simulated signals of SWAT-MODFLOW appeared more plausible than those of SWAT, and the SWAT-MODFLOW decrease in streamflow was much closer to the actual volume abstracted. The impact of drinking water abstraction on streamflow depletion simulated by SWAT was unrealistically low, and the streamflow increase caused by irrigation abstraction was exaggerated compared with SWAT-MODFLOW. We conclude that the further developed SWAT-MODFLOW model calibrated by PEST had a better hydrological simulation performance, wider possibilities for groundwater analysis, and much more realistic signals relative to the semi-distributed SWAT model when assessing the impacts of groundwater abstractions for either irrigation or drinking water on streamflow; hence, it has the potential to be a useful tool in the management of water resources in groundwater-affected catchments. However, this comes at the expense of higher computational demand and more time consumption.