Simulating future hydrological droughts and sediment yield by integrating different climate scenarios for a semiarid basin in Brazil

IF 3.9 3区环境科学与生态学 Q1 ENGINEERING, CIVIL

Stochastic Environmental Research and Risk Assessment Pub Date : 2024-08-12 DOI:10.1007/s00477-024-02777-1

Tatiane Gomes Frade, Celso Augusto Guimarães Santos, Richarde Marques da Silva

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Abstract

This paper presents an integrated simulation of future hydrological droughts using different climate scenarios for the Piancó River basin. Streamflow and sediment yield are estimated using the Soil and Water Assessment Tool (SWAT) model, and hydrological droughts are calculated using the Streamflow Drought Index (SDI). The study incorporates two future climate scenarios: RCP 4.5 (optimistic) and RCP 8.5 (pessimistic). The SDI is determined based on a series of simulated future flows to identify drought events within the basin. The results show that the model calibration and validation demonstrated excellent agreement with observed data (R² = 0.83, NSE = 0.82 for calibration and R² = 0.89, NSE = 0.77 for validation). When comparing the scenarios, reductions in flow volume by −75.86% and sediment yield by −86.5% are noted, indicating a significant decrease in sediment contribution to the outlet. Interestingly, the most critical years related to drought events, as determined by the SDI, do not coincide across the pessimistic and optimistic scenarios.

Graphical Abstract

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通过综合巴西一个半干旱盆地的不同气候情景，模拟未来的水文干旱和泥沙产量

本文采用不同的气候情景，对皮安科河流域未来的水文干旱进行了综合模拟。使用水土评估工具 (SWAT) 模型估算了溪流和泥沙产量，并使用溪流干旱指数 (SDI) 计算了水文干旱。研究采用了两种未来气候情景：RCP 4.5（乐观）和 RCP 8.5（悲观）。SDI 根据一系列模拟的未来流量确定，以识别流域内的干旱事件。结果表明，模型校准和验证与观测数据非常吻合（校准的 R² = 0.83，NSE = 0.82；验证的 R² = 0.89，NSE = 0.77）。在对各种方案进行比较时，发现流量减少了-75.86%，泥沙产量减少了-86.5%，这表明排入出口的泥沙量显著减少。有趣的是，由 SDI 确定的与干旱事件有关的最关键年份在悲观和乐观方案中并不一致。

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来源期刊

Stochastic Environmental Research and Risk Assessment 环境科学-工程：环境

CiteScore

7.10

自引率

9.50%

发文量

189

审稿时长

3.8 months

期刊介绍： Stochastic Environmental Research and Risk Assessment (SERRA) will publish research papers, reviews and technical notes on stochastic and probabilistic approaches to environmental sciences and engineering, including interactions of earth and atmospheric environments with people and ecosystems. The basic idea is to bring together research papers on stochastic modelling in various fields of environmental sciences and to provide an interdisciplinary forum for the exchange of ideas, for communicating on issues that cut across disciplinary barriers, and for the dissemination of stochastic techniques used in different fields to the community of interested researchers. Original contributions will be considered dealing with modelling (theoretical and computational), measurements and instrumentation in one or more of the following topical areas: - Spatiotemporal analysis and mapping of natural processes. - Enviroinformatics. - Environmental risk assessment, reliability analysis and decision making. - Surface and subsurface hydrology and hydraulics. - Multiphase porous media domains and contaminant transport modelling. - Hazardous waste site characterization. - Stochastic turbulence and random hydrodynamic fields. - Chaotic and fractal systems. - Random waves and seafloor morphology. - Stochastic atmospheric and climate processes. - Air pollution and quality assessment research. - Modern geostatistics. - Mechanisms of pollutant formation, emission, exposure and absorption. - Physical, chemical and biological analysis of human exposure from single and multiple media and routes; control and protection. - Bioinformatics. - Probabilistic methods in ecology and population biology. - Epidemiological investigations. - Models using stochastic differential equations stochastic or partial differential equations. - Hazardous waste site characterization.