A Process–Based Rating Curve to model suspended sediment concentration in Alpine environments

A Process-Based Rating Curve (PBRC) approach to simulate mean daily suspended sediment concentration (SSC) as a function of different sediment sources and their activation by erosive rainfall (ER), snowmelt (SM), and icemelt (IM) in an Alpine catchment is presented. Similarly to the traditional rating curve, the PBRC relates SSC to the three main hydroclimatic variables through power functions. We obtained the hydroclimatic variables from daily gridded datasets of precipitation and temperature, implementing a degree-day model to simulate spatially distributed snow accumulation and snow-ice melt. We calibrated the PBRC parameters by an Iterative Input Selection algorithm to capture the characteristic response time lags, and by a gradient-based nonlinear optimization method to minimize the errors between SSC observations and simulations. We apply our approach in the upper Rhône Basin, a large Alpine catchment in Switzerland. Results show that all three hydroclimatic processes ER, SM, and IM are significant predictors of mean daily SSC (explaining 75 %, 12 % and 3 % of the total observed variance). Despite not using discharge in prediction, the PBRC performs better than the traditional rating curve, especially during validation at the daily scale and in reproducing SSC seasonality. The characteristic time lags of the three variables in contributing to SSC reflect the typical flow concentration times of the corresponding hydrological processes in the basin. Erosive rainfall determines the daily variability of SSC, icemelt generates the highest SSC per unit of runoff, and snowmelt-driven fluxes represent the largest contribution to total suspended sediment yield. Finally, we show that the PBRC is able to simulate changes in SSC in the past 40 years in the Rhône Basin connected to air temperature rise, even though these changes are more gradual than those detected in observations. We argue that a sediment source perspective on suspended sediment transport such as the PBRC may be more suitable than traditional discharge-based rating curves to explore climate-driven changes in fine sediment dynamics in Alpine catchments. The PBRC approach can be applied to any Alpine catchment with a pluvio-glacio-nival hydrological regime and adequate hydroclimatic datasets.ISSN:1812-2116ISSN:1812-210

A spatially distributed conceptual model for estimating suspended sediment yield in Alpine catchments

ISSN:1029-7006ISSN:1607-796

Hydroclimatic control on suspended sediment dynamics of a regulated Alpine catchment: a conceptual approach

We analyse the control of hydroclimatic factors on suspended sediment concentration (SSC) in Alpine catchments by differentiating among the potential contributions of erosion and suspended sediment transport driven by erosive rainfall, defined as liquid precipitation over snow-free surfaces, ice melt from glacierized areas, and snowmelt on hillslopes. We account for the potential impact of hydropower by intercepting sediment fluxes originated in areas diverted to hydropower reservoirs, and by considering the contribution of hydropower releases to SSC. We obtain the hydroclimatic variables from daily gridded datasets of precipitation and temperature, implementing a degree-day model to simulate spatially distributed snow accumulation and snow–ice melt. We estimate hydropower releases by a conceptual approach with a unique virtual reservoir regulated on the basis of a target-volume function, representing normal reservoir operating conditions throughout a hydrological year. An Iterative Input Selection algorithm is used to identify the variables with the highest predictive power for SSC, their explained variance, and characteristic time lags. On this basis, we develop a hydroclimatic multivariate rating curve (HMRC) which accounts for the contributions of the most relevant hydroclimatic input variables mentioned above. We calibrate the HMRC with a gradient-based nonlinear optimization method and we compare its performance with a traditional discharge-based rating curve. We apply the approach in the upper Rhône Basin, a large Swiss Alpine catchment heavily regulated by hydropower. Our results show that the three hydroclimatic processes – erosive rainfall, ice melt, and snowmelt – are significant predictors of mean daily SSC, while hydropower release does not have a significant explanatory power for SSC. The characteristic time lags of the hydroclimatic variables correspond to the typical flow concentration times of the basin. Despite not including discharge, the HMRC performs better than the traditional rating curve in reproducing SSC seasonality, especially during validation at the daily scale. While erosive rainfall determines the daily variability of SSC and extremes, ice melt generates the highest SSC per unit of runoff and represents the largest contribution to total suspended sediment yield. Finally, we show that the HMRC is capable of simulating climate-driven changes in fine sediment dynamics in Alpine catchments. In fact, HMRC can reproduce the changes in SSC in the past 40 years in the Rhône Basin connected to air temperature rise, even though the simulated changes are more gradual than those observed. The approach presented in this paper, based on the analysis of the hydroclimatic control of suspended sediment concentration, allows the exploration of climate-driven changes in fine sediment dynamics in Alpine catchments. The approach can be applied to any Alpine catchment with a pluvio-glacio-nival hydrological regime and adequate hydroclimatic datasets.ISSN:1027-5606ISSN:1607-793

This Data supports the University of Southampton Doctoral Thesis "Robust optimization technique for hydropower optimization".

This data supports the University of Southampton Doctoral thesis &quot;Robust Optimization Technique for Hydropower Optimization&quot; by J Badrodin. The data are available in the literature (Anghileri, Castelletti et al., 2018) and on the website https://www.kraftwerkemattmarkag.ch/anlagen/. We made reasonable assumptions whenever information was not publicly available. The inflow scenarios used in the training and validation set were stochastically generated using the model published in Anghileri, Castelletti et al., 2018.</span

Determining effective forecast horizons for multi-purpose reservoirs with short- and long-term operating objectives

ISSN:1029-7006ISSN:1607-796

Alpine hydropower in the decline of the nuclear era: trade-off between revenue and production in the Swiss Alps

Hydropower systems contribute to the welfare of a country by producing renewable and clean electricity and by generating revenue. Market liberalization and increasing share of new renewable energy sources, with associated increase in price volatility, are profoundly reshaping hydropower operations in many countries where these developments have already taken place. In this evolving context, some European countries are phasing out nuclear power plants and looking for alternatives to replace the lost production share. Hydropower is one of the candidates, particularly in water-abundant hydrological regions, where large storage hydropower systems contribute a big share of the production. Yet, shifting current revenue-oriented operations toward a production-maximizing strategy might come to the cost of a reduction in income for hydropower companies. In this paper, we specifically explore trade-offbetween maximizing hydropower electricity production and revenue in deregulated markets. We focus on a case study in the Swiss Alps that can be considered as paradigmatic of most hydropower systems in mountainous regions worldwide. We developed a stochastic biobjective optimal control problem, which allows the design alternative hydropower operating strategies differently balancing electricity production and revenue maximization, accounting for both the variability of reservoir inflow and electricity price. Our results show that a production-driven operation might have strong consequences on the hydropower company income, suggesting that there is a low rate of substitution between the two objectives in the current energy market situation. The proposed approach can support policy makers in analyzing the dualism production/revenue in any hydropower system under complex natural and socioeconomic constraints and represents a benchmark to test different types of mechanisms to promote favorable economic conditions to hydropower companies to increase electricity production.</p

Trend detection in seasonal data: From hydrology to water resources

In this paper we investigate the relationship between hydro-climatic trends and their impacts on water resources at the basin scale, focusing on a catchment on the Italian and Swiss Alps in the period 1974-2010. More generally, we address the topic of trend detection in environmental time series combining novel and traditional tools in order to simultaneously tackle the issue of seasonality and interannual variability, which usually characterize natural processes. The paper's contribution is twofold. First, we propose a novel tool to be applied in Exploratory Data Analysis, named MASH (Moving Average over Shifting Horizon). It allows to simultaneously investigate the seasonality in the data and filter out the effects of interannual variability, thus facilitating trend detection. We describe how to combine the MASH with statistical trend detection tests, like the Mann-Kendall test, the Seasonal Kendall test, and the Linear Regression test, and Sen's method, to quantify the trends occurring in different seasons. Second, we estimate the impacts of hydrological changes in terms of water resources and we discuss their relevance from the water resources management perspective. We define and simulate a set of indicators of performances, resilience, reliability, and vulnerability, so to assess the ability of the water resources systems to absorb changes in the hydrological patterns. The analysis reveals that, in the case study area, statistically significant trends in hydro-climatic records have been undergoing in the last decades, although they have had limited impacts on water resources.</p

On the effects of adaptive reservoir operating rules in hydrological physically-based models

ISSN:1029-7006ISSN:1607-796

Informing the operations of water reservoirs over multiple temporal scales by direct use of hydro-meteorological data

Water reservoir systems may become more adaptive and reliable to external changes by enlarging the information sets used in their operations. Models and forecasts of future hydro-climatic and socio-economic conditions are traditionally used for this purpose. Nevertheless, the identification of skillful forecasts and models might be highly critical when the system comprises several processes with inconsistent dynamics (fast and slow) and disparate levels of predictability. In these contexts, the direct use of observational data, describing the current conditions of the water system, may represent a practicable and zero-cost alternative. This paper contrasts the relative contribution of state observations and perfect forecasts of future water availability in improving multipurpose water reservoirs operation over short- and long-term temporal scales. The approach is demonstrated on the snow-dominated Lake Como system, operated for flood control and water supply. The Information Selection Assessment (ISA) framework is adopted to retrieve the most relevant information to be used for conditioning the operations. By explicitly distinguishing between observational dataset and future forecasts, we quantify the relative contribution of current water system state estimates and perfect streamflow forecasts in improving the lake regulation with respect to both flood control and water supply. Results show that using the available observational data capturing slow dynamic processes, particularly the snow melting process, produces a 10% improvement in the system performance. This latter represents the lower bound of the potential improvement, which may increase to the upper limit of 40% in case skillful (perfect) long-term streamflow forecasts are used.</p

Descriptive or normative: How does reservoir operations modeling influence hydrological simulations under climate change?

Human activities have a strong influence on the hydrological cycle altering natural patterns of evapotranspiration, soil infiltration capacity, ice cover, groundwater distribution, and, ultimately, streamflow at different spatio-temporal scales. Yet, modelling human activities and the associated impacts are often given a secondary importance in hydrological models with respect to the high-fidelity characterization of natural processes, especially at the catchment scale. While this has little or no influence on model accuracy when modelling pristine watersheds, it remarkably deteriorates the model performance in river basins with a considerable anthropogenic footprint. Operations of water infrastructures within a watershed, e.g., a dam or a diversion dam, are commonly modelled based on observational data, when available. This reproduces to some extent the historical decisions, but might be inadequate to simulate operations outside of historical climate or socio-economic conditions. In this paper, we compare a descriptive approach traditionally adopted in hydrological models, where reservoir operations are determined by tracking the historical average release, and a normative approach, where the operations are dynamically conditioned upon the reservoir storage and can adapt to the climate and socio-economic conditions influencing the reservoir operations. We contrast these two approaches by assessing the reservoir dynamics and the impacts on the downstream river system across time scales, from daily to seasonal. We first discuss the accuracy of the two approaches in reproducing historical observations. Then, we explore their potential in anticipating the impacts of future reservoir operations when considering climate and socio-economic change scenarios, thus testing the approaches in decision making contexts increasingly altered with respect to the historical one. We critically present the advantages and disadvantages of either approach, thus contributing to clarify the importance of adopting an appropriate approach to model reservoir operations when reconstructing past dynamics or anticipating future dynamics of catchments impacted by human activities.</p