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Monthly and seasonal streamflow forecasting of large dryland catchments in Brazil

Journal of arid Land 2021年第3期13卷 205-223页

作者： Alexandre C COSTA Alvson B S ESTACIO Francisco de A de SOUZA FILHO Iran E LIMA neto Institute of Engineering and Sustainable Development University of International Integration of the Afro-Brazilian LusophonyRedençãoCEP 62.790-970Brazil Department of Hydraulic Engineering and Environment Federal University of CearáFortalezaCEP 60.451-970Brazil

Streamflow forecasting in drylands is *** are scarce,catchments are highly humanmodified and streamflow exhibits strong nonlinear responses to *** goal of this study was to evaluate the monthly and seasonal streamflow forecasting in two large catchments in the Jaguaribe River Basin in the Brazilian semi-arid *** adopted four different lead times:one month ahead for monthly scale and two,three and four months ahead for seasonal *** gaps of the historic streamflow series were filled up by using rainfall-runoff ***,time series model techniques were applied,i.e.,the locally constant,the locally averaged,the k-nearest-neighbours algorithm(k-NN)and the autoregressive(ar)*** criterion of reliability of the validation results is that the forecast is more skillful than streamflow *** approach outperformed the streamflow climatology for all monthly *** average,the former was 25%better than the *** seasonal streamflow forecasting(SSF)was also reliable(on average,20%better than the climatology),failing slightly only for the high flow season of one catchment(6%worse than the climatology).Considering an uncertainty envelope(probabilistic forecasting),which was considerably narrower than the data standard deviation,the streamflow forecasting performance increased by about 50%at both *** forecast errors were mainly driven by the streamflow intra-seasonality at monthly scale,while they were by the forecast lead time at seasonal *** best-fit and worst-fit time series model were the k-NN approach and the ar model,*** rainfall-runoff modelling outputs played an important role in improving streamflow forecasting for one streamgauge that showed 35%of data *** developed data-driven approach is mathematical and computationally very simple,demands few resources to accomplish its operational implementation and is applicable to other dryland *** findings may be part of drou

关键词： nonlinear time series analysis probabilistic streamflow forecasting reconstructed streamflow data dryland hydrology rainfall-runoff modelling stochastic dynamical systems

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Hydrological Processes and Climate Change in Hydrographic Regions of Brazil

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Journal of Water Resource and Protection 2016年第12期8卷 1103-1127页

作者： Alfredo Ribeiro neto Adriano Rolim da Paz José Antonio Marengo Sin Chan Chou Civil and Environmental Engineering Department Federal University of Pernambuco Recife Brazil Civil and Environmental Engineering Department Federal University of Paraíba Joao Pessoa Brazil National Center for Monitoring and Early Warning of Natural Disasters S&#227o José dos Campos Brazil Center for Weather Forecasts and Climate Studies National Institute for Space Research Cachoeira Paulista Brazil

The objective of this work is to assess the impacts of IPCC ar5 climate change scenarios on water resources and hydrological processes across the entire Brazilian territory. Hydrological simulations are carried out in total drainage area of about 11,535,645 km2 and average stream flow of about 272,460 m3/s. The study area consists of different climates and land covers such as the Amazon Forest, Northeast Semiarid, Brazilian Savannah, Pantanal wetlands and temperate climate in the South. The atmospheric forcing to drive the large-scale hydrological model MGB-IPH is derived from the downscaling of two global climate models, HadGEM2-ES and MIROC5, by the Eta Regional Climate Model, at 20 km resolution. The Eta model provided the downscaling of the baseline (1961-1990) and three time-slices (2011-2040, 2041-2070 and 2071-2099). These projections adopted two emission scenarios, the RCP 4.5 and RCP 8.5. The change in the average and extremes of precipitation, evapotranspiration, rates of river discharge and soil moisture were assessed. The simulations showed the response of the hydrographic regions due to change of precipitation and potential evapotranspiration in the scenarios. Water availability decreases in almost the entire study area (exception for the South) and the major basins for hydroelectric power generation are affected. The Northwest, Amazon and a small area along the Northeast Atlantic coast exhibited intensification of the extremes discharges, where the anomaly is positive for high-flow (Q10) and negative for low-flow (Q95). The results highlight the most climatic sensitive regions in Brazil in terms of hydrological variables and water resources.

关键词： Hydrological Modelling IPCC Scenarios Climate Change Impacts

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