Simple and Low-Cost Procedure for Monthly and Yearly Streamflow Forecasts during the Current Hydrological Year

Estimation of the spatiotemporal dynamic of snow water equivalent at mountain range scale under data scarcity

The snow dynamics in alpine systems play a significant role in the hydrosphere, biosphere, and anthroposphere interfaces of these regions. The storage of water resources as snow is essential for ecosystems, human consumption, tourism, and hydropower in many areas. However, snow data are usually scarce due to poor accessibility, difficulties to maintain monitoring system under harsh climatic conditions and limited economic funds. Most of the scientific studies aimed to quantify water stored as snow are carried out at small or medium spatial scales, but few analyses are done for the whole mountain ranges. The main goal of this work is to propose a general parsimonious methodology to estimate snow water equivalent under data scarcity for the Sierra Nevada mountain range (Spain). The methodology is easily transferable to any other study areas. It combines a dynamic regression approach of snow depth from punctual data, snow cover area data from the MODIS satellite and simulations of snow density from a coupled mass and energy balance model. The regression model includes two kinds of explanatory variables (steady and non-steady) to assess the snow depth dynamics. The dynamic of the snow density in the mountain range has been obtained using a physically based simulation driven by climate model data for the Iberian Peninsula. These three variables (snow depth, snow cover area and snow density) have been used to obtain spatially distributed series of snow water equivalent for the whole mountain range. The proposed solution allows studying the snow water equivalent distribution, duration of the snow cover and number of accumulation and melting days for different snow seasons. The mean accumulated snow water equivalent per season in the historical period is 330 Hm3 and the maximum of 480 Hm3, which is a significant amount of resources in an area characterized by limited water availability.

Short-Term River Flow Forecasting Framework and Its Application in Cold Climatic Regions

Catchments located in cold weather regions are highly influenced by the natural seasonality that dictates all hydrological processes. This represents a challenge in the development of river flow forecasting models, which often require complex software that use multiple explanatory variables and a large amount of data to forecast such seasonality. The Athabasca River Basin (ARB) in Alberta, Canada, receives no or very little rainfall and snowmelt during the winter and an abundant rainfall–runoff and snowmelt during the spring/summer. Using the ARB as a case study, this paper proposes a novel simplistic method for short-term (i.e., 6 days) river flow forecasting in cold regions and compares existing hydrological modelling techniques to demonstrate that it is possible to achieve a good level of accuracy using simple modelling. In particular, the performance of a regression model (RM), base difference model (BDM), and the newly developed flow difference model (FDM) were evaluated and compared. The results showed that the FDM could accurately forecast river flow (ENS = 0.95) using limited data inputs and calibration parameters. Moreover, the newly proposed FDM had similar performance to artificial intelligence (AI) techniques, demonstrating the capability of simplistic methods to forecast river flow while bypassing the fundamental processes that govern the natural annual river cycle.

Drought Management Planning Policy: From Europe to Spain

Climate change is anticipated to exacerbate the frequency, the intensity, and the duration of droughts, especially in Mediterranean countries. This might lead to more serious water scarcity episodes and fierce competition among water users. Are we really prepared to deal efficiently with droughts and water scarcity events? This paper sheds light on this question by reviewing the evolution of European drought management planning policy, recently developed scientific and technical advances, technical guidance documents, and an extensive number of journal papers. More specifically, Spain presents an ideal context to assess how drought risk has been historically addressed because this country has periodically suffered the impacts of intense droughts and water scarcity episodes, and has developed a long track record in water legislation, hydrological planning, and drought risk management strategies. The most recent Drought Management Plans (DMPs) were approved in December 2018. These include an innovative common diagnosis system that distinguishes droughts and water scarcity situations in terms of indicators, triggers, phases, and actions. We can conclude that DMP should be a live and active document able to integrate updated knowledge. The DMP needs also to set out a clear strategy in terms of water use priorities, drought monitoring systems, and measures in each river basin in order to avoid generalist approaches and possible misinterpretation of the DMP that could lead to increase existing and future conflicts.

Hydrological Risk Analysis of Dams: The Influence of Initial Reservoir Level Conditions

In this paper, we present a method to assess the influence of the initial reservoir level in hydrological dam safety and risk analysis. Traditionally, in professional practice, the procedures applied are basically deterministic. Several physical processes are defined deterministically, according to the criteria of the designer (usually in the conservative side), although there is a high degree of uncertainty regarding these processes. A relevant variable is the reservoir level considered at the beginning of flood events. Hydrological dam safety assessment methods traditionally assume that the reservoir is initially full when it receives the design flood, thus, staying in the conservative side when designing a new dam. However, the distribution of reservoir levels at the beginning of flood episodes takes more importance for evaluating the real risk for the dams in operation. We analyzed three different scenarios—initial reservoir level equal to maximum normal level, equal to a maximum conservation level, and following the probability distribution from the historical records. To do so, we presented a method applied to a gated-spillway dam located in the Tagus river basin. A set of 100,000 inflow hydrographs was generated through a Monte Carlo procedure, by reproducing the statistics of the main observed hydrograph characteristics—peak flow, volume, and duration. The set of 100,000 hydrographs was routed through the reservoir applying the Volumetric Evaluation Method as a flood control strategy. In order to compare the three scenarios, we applied an economic global risk index. The index combines the hydrological risk for the dam, linked to the maximum water level reached in the reservoir, during the flood routing, and the flood risk in the downstream river reach, linked to the discharge releases from the dam. The results showed the importance of accounting for the fluctuation of initial reservoir levels, for assessing the risk related to hydrological dam safety. Furthermore, a procedure to quantify the uncertainty associated with the effects of initial reservoir level on hydrological dam safety, has been proposed.