Abstract:River flow from glacierized areas in the Himalaya is influenced both by intra-annual variations in precipitation and energy availability, and by longer term changes in storage of water as glacier ice. High specific discharge from ice melt often dominates flow for considerable distances downstream, particularly where other sources of runoff are limited, providing a major water resource. Should Himalayan glaciers continue to retreat rapidly, water shortages might be widespread within a few decades. However, given the difference in climate between the drier western and monsoonal eastern ends of the region, future warming is unlikely to affect river flow uniformly throughout.A simple temperature-index-based hydro-glaciological model, in which glacier dimensions are allowed to decline through time, has been developed with a view to assessing, in data-sparse areas, by how much and when climate warming will reduce Himalayan glacier dimensions and affect downstream river flows. Two glaciers having the same initial geometries were located (one each) in the headwaters of two identical nests of hypothetical catchments, representing contrasting climates in the west and east of the region. The hypothetical catchments were nested such that percentage ice cover declined with increasing basin area. Model parameters were validated against available but limited mass-balance and river flow measurements. The model was applied for 150 years from an arbitrary start date (1990), first with standard-period climate data and then with application of a 0Ð06°C year 1 transient climatic warming scenario.Under this warming scenario, Himalayan rivers fed by large glaciers descending through considerable elevation range will respond in a broadly similar manner, except that summer snowfall in the east will suppress the rate of initial flow increase, delay peak discharge and postpone eventual disappearance of the ice. Impacts of declining glacier area on river flow will be greater in smaller and more highly glacierized basins in both the west and east, and in the west, where precipitation is scarce, for considerable distances downstream. Crown
This paper examines the spatial and temporal development of streamflow droughts in Europe over the last 40 years, differentiating the climatic factors that drive drought formation from catchment controls on drought manifestation. A novel approach for quantifying and comparing streamflow and precipitation depletion is presented. This approach considers atypical flow or rainfall events, as well as more severe droughts, regardless of the season in which they occur (although unlikely to constitute drought in an operational sense, sustained atypical flows are important with regard to understanding how droughts arise and develop).The amount of flow depletion is quantified at daily resolution based on the standardised departure from the mean day d flow, or flow anomaly. The index was derived for 2780 gauging points within north-west Europe using data from the FRIEND European Water Archive for the 1960-1995 period. Using a simple interpolation procedure these data were used to produce a time-series of grids, with a cell size of 18 km 2 , showing the spatial distribution of flow anomaly over the study area. A similar approach was used to characterise monthly precipitation anomalies, based on existing grid data (see New et al., 2000). The grids were analysed chronologically to examine the spatial and temporal coherency of areas showing large flow and/or precipitation anomalies, focussing on drought development during the 1975-1976 and 1989-1990 periods. Using a threshold approach, in which an anomaly of 2 standard deviations represents the onset of drought conditions, indices were developed to describe the time-varying extent and areal-severity (flow deficit) of streamflow and precipitation drought. Similar indices were used to describe how the magnitude and temporal variation of flow depletion varied spatially.In terms of streamflow depletion, the 1976 drought was found to be a highly coherent event, having a well defined start (in January 1976) and end (in September 1976). The worst and most persistent streamflow droughts occurred in southern England and northern France. Central parts of Europe experienced only severe streamflow depletion during the 'height' of the drought in June, July and August when there was negligible precipitation across large areas of Europe. In contrast, the 1989/90 period was characterised by a series of shorter and less severe droughts, with much greater variability over time. The relationship between precipitation drought and streamflow drought was less clear, which might have resulted from periods of precipitation depletion occurring randomly in time. Particularly high levels of streamflow drought were again observed in southern England and northern France.Several possible explanations for the increased drought occurrence over southern England and northern France were investigated using data from the 1976 event. However, immediately antecedent precipitation deficits could not explain the level of streamflow depletion which appears to have been enhanced by decreased discharge of grou...
The flow regime of a river can be described using the flow duration curve (FDC), which represents the frequency distribution of flows and can be derived from gauged data. Many resource assessments are required where gauged data are limited or unavailable, thus models for predicting FDCs in ungauged catchments are required. In semiarid environments, such as parts of southern Portugal, river flows often become zero for significant periods of time. This makes modelling the discontinuities in the flow regime using commonly used continuous distributions more difficult. This paper presents the derivation of a regionalized model (from a data set of 67 catchments) for predicting FDCs for ungauged catchments in Portugal, which may be ephemeral. The approach uses the theory of total probability to combine a model for predicting the percentage of time the river is dry with a model for predicting an FDC for the non-zero period. These component parts can be modelled separately, relating them to catchment characteristics such as hydrogeology and climate.Key words theory of total probability; multiple regression analysis; flow duration curve; ungauged catchments; ephemeral streams; Portugal Estimation de la courbe des débits classés pour des bassins versants éphémères du PortugalRésumé: Le régime d'écoulement d'une rivière peut être décrit par la courbe des débits classés (CDC), qui représente la distribution de fréquence des débits et qui peut être déduite de données jaugées. Cependant, de nombreuses évaluations de la ressource sont requises en des sites où les données jaugées sont limitées ou non disponibles, ce qui rend nécessaires des modèles de prédétermination des CDC en bassins versants non jaugés. Dans des environnements semi-arides, comme par exemple dans certaines régions du sud du Portugal, les écoulements des cours d'eau deviennent souvent nuls pendant des laps de temps significatifs. Cela rend la modélisation des discontinuités du régime d'écoulement plus difficile avec les approches basées sur les distributions continues couramment utilisées. Cet article présente la déduction d'un modèle régional (en utilisant un jeu de données de 67 bassins versants) pour prédéterminer les CDC de bassins non jaugés au Portugal, y compris de bassins à écoulement éphémère. L'approche est basée sur la théorie de la probabilité totale pour combiner un modèle prédéterminant le pourcentage de temps pendant lequel le cours d'eau est sec, et un modèle prédéterminant une CDC relative à la période où les débits sont non nuls. Ces différentes parties peuvent être modélisées séparément, en les reliant aux caractéristiques des bassins versants comme l'hydrogéologie ou le climat.
The Himalayan region of Nepal and northern India experiences hydrological extremes from monsoonal floods during July to September, when most of the annual precipitation falls, to periods of very low flows during the dry season (December to February). While the monsoon floods cause acute disasters such as loss of human life and property, mudslides and infrastructure damage, the lack of water during the dry season has a chronic impact on the lives of local people. The management of water resources in the region is hampered by relatively sparse hydrometerological networks and consequently, many resource assessments are required in catchments where no measurements exist. A hydrological model for estimating dry season flows in ungauged catchments, based on recession curve behaviour, has been developed to address this problem. Observed flows were fitted to a second order storage model to enable average annual recession behaviour to be examined. Regionalised models were developed, using a calibration set of 26 catchments, to predict three recession curve parameters: the storage constant; the initial recession flow and the start date of the recession. Relationships were identified between: the storage constant and catchment area; the initial recession flow and elevation (acting as a surrogate for rainfall); and the start date of the recession and geographic location. An independent set of 13 catchments was used to evaluate the robustness of the models. The regional models predicted the average volume of water in an annual recession period (1st of October to the 1st of February) with an average error of 8%, while mid-January flows were predicted to within ±50% for 79% of the catchments in the data set.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.