当前的研究重点是分析气候变化和土地利用/土地覆盖(LULC)变化对Puthimari盆地沉积物产量的影响,雅鲁藏布江的喜马拉雅东部分水岭,使用混合SWAT-ANN模型方法。该分析被精心分为三个不同的时间跨度:2025-2049、2050-2074和2075-2099。这种创新的方法整合了两种代表性浓度路径(RCP4.5和RCP8.5)下的多种气候模型的见解,以及通过元胞自动机马尔可夫模型生成的LULC投影。通过结合土壤和水评估工具(SWAT)和人工神经网络(ANN)技术的优势,这项研究旨在提高沉积物产量模拟的准确性,以应对不断变化的环境条件。混合模型的ANN分量采用具有外部输入的非线性自回归(NARX)方法。与单独使用SWAT模型相比,采用混合SWAT-ANN方法似乎在提高沉积物产量模拟的准确性方面特别有效,与独立SWAT模型的0.35相比,混合模型的确定系数较高,为0.74。在RCP4.5情景的背景下,在2075-99年间,研究发现沉积物产量增加了29.34%,伴随着印度季风季节流量和降雨量同时上升42.74%和27.43%,从六月到九月。相比之下,在RCP8.5场景下,在同一时期,沉积物产量的增加,放电,季风季节的降雨量为116.56%,103.28%,和64.72%,分别。本研究对Puthimari河流域泥沙供应影响因素的综合分析填补了一个重要的知识空白,并为设计主动洪水和侵蚀管理策略提供了宝贵的见解。这项研究的结果对于了解Puthimari盆地对气候和土地利用变化的脆弱性至关重要,并将这些发现纳入政策和决策过程,面对未来的水文和环境挑战,利益相关者可以努力增强韧性和可持续性。
The current study focuses on analyzing the impacts of climate change and land use/land cover (LULC) changes on sediment yield in the Puthimari basin, an Eastern Himalayan sub-watershed of the Brahmaputra, using a hybrid
SWAT-ANN model approach. The analysis was meticulously segmented into three distinct time spans: 2025-2049, 2050-2074, and 2075-2099. This innovative method integrates insights from multiple climate models under two Representative Concentration Pathways (RCP4.5 and RCP8.5), along with LULC projections generated through the Cellular Automata Markov model. By combining the strengths of the Soil and Water Assessment Tool (
SWAT) and artificial neural network (ANN) techniques, the study aims to improve the accuracy of sediment yield simulations in response to changing environmental conditions. The non-linear autoregressive with external input (NARX) method was adopted for the ANN component of the hybrid model. The adoption of the hybrid
SWAT-ANN approach appears to be particularly effective in improving the accuracy of sediment yield simulation compared to using the
SWAT model alone, as evidenced by the higher coefficient of determination value of 0.74 for the hybrid model compared to 0.35 for the standalone
SWAT model. In the context of the RCP4.5 scenario, during 2075-99, the study noted a 29.34% increase in sediment yield, accompanied by simultaneous rises of 42.74% in discharge and 27.43% in rainfall during the Indian monsoon season, spanning from June to September. In contrast, under the RCP8.5 scenario, for the same period, the increases in sediment yield, discharge, and rainfall for the monsoon season were determined to be 116.56%, 103.28%, and 64.72%, respectively. The present study\'s comprehensive analysis of the factors influencing sediment supply in the Puthimari River basin fills an important knowledge gap and provides valuable insights for designing proactive flood and erosion management strategies. The findings from this research are crucial for understanding the vulnerability of the Puthimari basin to climate and land use changes, and by incorporating these findings into policy and decision-making processes, stakeholders can work towards enhancing resilience and sustainability in the face of future hydrological and environmental challenges.