Abstract

Accurately forecasting streamflow values is essential to achieve an efficient, integrated water resources management strategy and to provide consistent support to water decision-makers. We present a simple, low-cost, and robust approach for forecasting monthly and yearly streamflows during the current hydrological year, which is applicable to headwater catchments. The procedure innovatively combines the use of well-known regression analysis techniques, the two-parameter Gamma continuous cumulative probability distribution function and the Monte Carlo method. Several model performance statistics metrics (including the Coefficient of Determination R2; the Root-Mean-Square Error RMSE; the Mean Absolute Error MAE; the Index of Agreement IOA; the Mean Absolute Percent Error MAPE; the Coefficient of Nash-Sutcliffe Efficiency NSE; and the Inclusion Coefficient IC) were used and the results showed good levels of accuracy (improving as the number of observed months increases). The model forecast outputs are the mean monthly and yearly streamflows along with the 10th and 90th percentiles. The methodology has been successfully applied to two headwater reservoirs within the Guadalquivir River Basin in southern Spain, achieving an accuracy of 92% and 80% in March 2017. These risk-based predictions are of great value, especially before the intensive irrigation campaign starts in the middle of the hydrological year, when Water Authorities have to ensure that the right decision is made on how to best allocate the available water volume between the different water users and environmental needs.

Highlights

  • Nowadays, water authorities and decision-makers are facing considerable challenges in achieving a sustainable and integrated water resources management system, especially, in water-stressed areas

  • This research contributes towards the development of a user-guided, novel, simple, low cost, and robust methodology to forecast streamflows within the current hydrological year

  • This research contributes towards the development of a user-guided, simple, low cost, and robust procedure for forecasting monthly and annual streamflows during the current hydrological year

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Summary

Introduction

Water authorities and decision-makers are facing considerable challenges in achieving a sustainable and integrated water resources management system, especially, in water-stressed areas They must make responsible management decisions on the optimum allocation of the available water volume from a wide range of possible sources (regulated or non-regulated rivers, groundwater resources, water re-use schemes, desalination plants, etc.) between the demands of, usually, multi-sectoral water users (urban, agriculture, industry, tourism, energy, etc.). Water 2018, 10, 1038 the effects of climate change on spatial distribution and temporal climate variability, coupled with an ever-increasing population, are altering traditional approaches to water resources planning, management, and decision processes [1,2] To cope with this situation, a wide variety of conservation policies from supply augmentation (i.e., new infrastructures, such as reservoirs, desalination plants, rainwater harvesting, grey and black water reuse schemes, water transfers, groundwater recharge, etc.) to water demand reduction (i.e., water use efficiency, water restrictions, pricing policies, governance, etc.) can be adopted at the basin scale [3]. Long-term forecasting is key for planning investment in new strategic water infrastructures (such as reservoirs or water transfers between different catchments) as well as to inform the preparation of the River Basin Management Plans

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