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Calibration of Land-Use-Dependent Evaporation Parameters in Distributed Hydrological Models Using MODIS Evaporation Time Series Data 利用 MODIS 蒸发时间序列数据校准分布式水文模型中与土地利用相关的蒸发参数
IF 3.2 Q2 WATER RESOURCES Pub Date : 2023-11-21 DOI: 10.3390/hydrology10120216
M. Casper, Zoé Salm, O. Gronz, Christopher Hutengs, Hadis Mohajerani, Michael Vohland
The land-use-specific calibration of evapotranspiration parameters in hydrologic modeling is challenging due to the lack of appropriate reference data. We present a MODIS-based calibration approach of vegetation-related evaporation parameters for two mesoscale catchments in western Germany with the physically based distributed hydrological model WaSiM-ETH. Time series of land-use-specific actual evapotranspiration (ETa) patterns were generated from MOD16A2 evapotranspiration and CORINE land-cover data from homogeneous image pixels for the major land-cover types in the region. Manual calibration was then carried out for 1D single-cell models, each representing a specific land-use type based on aggregated 11-year mean ETa values using SKout and PBIAS as objective functions (SKout > 0.8, |PBIAS| < 5%). The spatio-temporal evaluation on the catchment scale was conducted by comparing the simulated ETa pattern to six daily ETa grids derived from LANDSAT data. The results show a clear overall improvement in the SPAEF (spatial efficiency metric) for most land-use types, with some deficiencies for two scenes in spring and late summer due to phenological variation and a particularly dry hydrological system state, respectively. The presented method demonstrates a significant improvement in the simulation of ETa regarding both time and spatial scale.
由于缺乏适当的参考数据,在水文模型中针对特定土地利用校准蒸散参数具有挑战性。我们利用基于物理的分布式水文模型 WaSiM-ETH,为德国西部的两个中尺度集水区提供了一种基于 MODIS 的植被相关蒸发参数校准方法。根据 MOD16A2 蒸散和 CORINE 土地覆盖数据,从该地区主要土地覆盖类型的同质图像像素中生成了特定土地利用实际蒸散(ETa)模式的时间序列。然后,根据 11 年平均蒸散发总值,以 SKout 和 PBIAS 为目标函数(SKout > 0.8,|PBIAS| < 5%),对代表特定土地利用类型的一维单细胞模型进行手动校准。通过将模拟 ETa 模式与 LANDSAT 数据得出的六个日 ETa 网格进行比较,在流域范围内进行了时空评估。结果表明,大多数土地利用类型的 SPAEF(空间效率指标)总体上有明显改善,但春季和夏末的两个场景由于物候变化和特别干旱的水文系统状态而分别存在一些不足。所提出的方法在时间和空间尺度上都明显改善了 ETa 的模拟。
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引用次数: 0
Analysis of Water Volume Required to Reach Steady Flow in the Constant Head Well Permeameter Method 恒水头水井渗透法达到稳定流所需的水量分析
IF 3.2 Q2 WATER RESOURCES Pub Date : 2023-11-18 DOI: 10.3390/hydrology10110214
A. Amoozegar, J. Heitman
The most common method for in situ measurement of saturated hydraulic conductivity (Ksat) of the vadose zone is the constant head well permeameter method. Our general objective is to provide an empirical method for determining volume of water required for measuring Ksat using this procedure. For one-dimensional infiltration, steady state reaches as time (t) → ∞. For three-dimensional water flow from a cylindrical hole under a constant depth of water, however, steady state reaches rather quickly when a saturated bulb forms around the hole. To reach a quasi-steady state for measuring Ksat, we assume an adequate volume of water is needed to form the saturated bulb around the hole and increase the water content outside of the saturated bulb within a bulb-shaped volume of soil, hereafter, referred to as wetted soil volume. We determined the dimensions of the saturated bulb using the Glover model that is used for calculating Ksat. We then used the values to determine the volume of the saturated and wetted bulbs around the hole. The volume of water needed to reach a quasi-steady state depends on the difference between the soil saturated and antecedent water content (Δθ). Based on our analysis, between 2 and 5 L of water is needed to measure Ksat when Δθ varies between 0.1 and 0.4 m3 m−3, respectively.
现场测量浸润带饱和导流系数(Ksat)的最常用方法是恒定水头井渗透仪法。我们的总体目标是提供一种经验方法,用于确定使用该方法测量 Ksat 所需的水量。对于一维渗透,当时间 (t) → ∞ 时达到稳定状态。然而,对于在恒定水深下从圆柱形孔洞流出的三维水流,当孔洞周围形成饱和水球时,水流很快就会达到稳定状态。为了达到测量 Ksat 的准稳态,我们假定需要足够的水量在孔周围形成饱和球,并增加饱和球外球状土壤体积(以下称为湿润土壤体积)中的含水量。我们使用用于计算 Ksat 的格洛弗模型确定了饱和球的尺寸。然后,我们利用这些数值来确定孔洞周围饱和球茎和湿润球茎的体积。达到准稳定状态所需的水量取决于土壤饱和含水量与先期含水量之间的差值 (Δθ)。根据我们的分析,当 Δθ 在 0.1 至 0.4 m3 m-3 之间变化时,测量 Ksat 分别需要 2 至 5 L 的水。
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引用次数: 0
General Extreme Value Fitted Rainfall Non-Stationary Intensity-Duration-Frequency (NS-IDF) Modelling for Establishing Climate Change in Benin City 用于确定贝宁市气候变化的一般极值拟合降雨非静态强度-持续时间-频率 (NS-IDF) 模型
IF 3.2 Q2 WATER RESOURCES Pub Date : 2023-11-17 DOI: 10.11648/j.hyd.20231104.13
Masi G. Sam, Ify L. Nwaogazie, C. Ikebude
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引用次数: 0
Groundwater Bodies Subdivision in Corsica: A Critical Approach Based on Multivariate Water Quality Criteria Using Large Database 科西嘉地下水体细分:利用大型数据库,基于多元水质标准的关键方法
IF 3.2 Q2 WATER RESOURCES Pub Date : 2023-11-15 DOI: 10.3390/hydrology10110213
Hajar Lazar, Meryem Ayach, A. Barry, Ismail Mohsine, Abdessamad Touiouine, F. Huneau, Christophe Mori, É. Garel, I. Kacimi, Vincent Valles, L. Barbiero
The cross-referencing of two databases, namely the compartmentalization into groundwater bodies (GWB) and the quality monitoring (2830 observations including 15 physico-chemical and bacteriological parameters, on 662 collection points and over a period of 27 years) is applied to better understand the diversity of the waters of the island of Corsica (France) and to facilitate the surveillance and quality monitoring of the groundwater resource. Data conditioning (log-transformation), dimensional reduction (PCA), classification (AHC) and then quantification of the information lost during grouping (ANOVA), highlight the need to sub-divide the groundwater bodies in the crystalline part of the island in order to take better account of lithological diversity and other environmental factors (slope, altitude, soil thickness, etc.). The compartmentalization into 15 units, mainly based on structural geology, provides less information than the grouping into 12 units after subdivision of the crystalline region. The diversity of the waters in terms of chemical and bacteriological composition is discussed, and the results encourage a review of the compartmentalization of the island’s GWBs, with a view to more targeted monitoring based on this diversity.
为了更好地了解科西嘉岛(法国)水域的多样性,促进对地下水资源的监控和质量监测,我们对两个数据库进行了交叉对比,即地下水体(GWB)的划分和质量监测(2830 次观测,包括 15 个物理化学和细菌学参数,共 662 个采集点,历时 27 年)。数据调节(对数变换)、降维(PCA)、分类(AHC),然后对分组过程中丢失的信息进行量化(方差分析),突出了对科西嘉岛结晶部分地下水体进行细分的必要性,以便更好地考虑岩性多样性和其他环境因素(坡度、海拔、土壤厚度等)。主要根据地质构造将其划分为 15 个单元,提供的信息少于将结晶区域划分为 12 个单元后提供的信息。讨论了水域在化学和细菌组成方面的多样性,结果鼓励对岛上全球水文地质观测站的分区进行审查,以便根据这种多样性进行更有针对性的监测。
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引用次数: 0
An Open-Source Cross-Section Tool for Hydrodynamic Model Geometric Input Development 用于开发水动力学模型几何输入的开源截面工具
IF 3.2 Q2 WATER RESOURCES Pub Date : 2023-11-14 DOI: 10.3390/hydrology10110212
B. Tom, Minxue He, Prabhjot Sandhu
Hydrodynamic models are widely used in simulating water dynamics in riverine and estuarine systems. A reasonably realistic representation of the geometry (e.g., channel length, junctions, cross-sections, etc.) of the study area is imperative for any successful hydrodynamic modeling application. Typically, hydrodynamic models do not digest these data directly but rely on pre-processing tools to convert the data to a readable format. This study presents a parsimonious open-source and user-friendly Java software tool, the Cross-Section Development Program (CSDP), that is developed by the authors to prepare geometric inputs for hydrodynamic models. The CSDP allows the user to select bathymetry data collected in different years by different agencies and create cross-sections and computational points in a channel automatically. This study further illustrates the application of this tool to the Delta Simulation Model II, which is the operational forecasting and planning hydrodynamic and water quality model developed for the Sacramento–San Joaquin Delta in California, United States. Model simulations on water levels and flow rates at key stations are evaluated against corresponding observations. The simulations mimic the patterns of the corresponding observations very well. The square of the correlation coefficient is generally over 0.95 during the calibration period and over 0.80 during the validation period. The absolute bias is generally less than 5% and 10% during the calibration and validation periods, respectively. The Kling–Gupta efficiency index is generally over 0.70 during both calibration and validation periods. The results illustrate that CSDP can be efficiently applied to generate geometric inputs for hydrodynamic models.
水动力模型被广泛用于模拟河流和河口系统中的水动力学。研究区域的几何形状(如河道长度、交汇点、横截面等)的合理真实再现是水动力模型成功应用的必要条件。通常情况下,水动力模型不会直接消化这些数据,而是依靠预处理工具将数据转换为可读格式。本研究介绍了作者开发的一种简便的开源、用户友好型 Java 软件工具--断面开发程序(CSDP),用于为水动力学模型准备几何输入。CSDP 允许用户选择不同机构在不同年份收集的水深测量数据,并自动创建河道横断面和计算点。本研究进一步说明了该工具在三角洲模拟模型 II 中的应用,该模型是为美国加利福尼亚州萨克拉门托-圣华金三角洲开发的运行预测和规划水动力及水质模型。该模型是为美国加利福尼亚州萨克拉门托-圣华金三角洲开发的业务预报和规划水动力及水质模型。模拟结果很好地模拟了相应观测数据的模式。在校准期间,相关系数的平方一般超过 0.95,在验证期间超过 0.80。在校准期和验证期,绝对偏差一般分别小于 5%和 10%。在校准和验证期间,Kling-Gupta 效率指数一般都超过 0.70。结果表明,CSDP 可以有效地用于生成水动力模型的几何输入。
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引用次数: 0
Investigating Multilayer Aquifer Dynamics by Combining Geochemistry, Isotopes and Hydrogeological Context Analysis 结合地球化学、同位素和水文地质背景分析研究多层含水层动态
Q2 WATER RESOURCES Pub Date : 2023-11-13 DOI: 10.3390/hydrology10110211
Francis Proteau-Bedard, Paul Baudron, Nicolas Benoit, Miroslav Nastev, Ryan Post, Janie Masse-Dufresne
Geochemical tracers have the potential to provide valuable insights for constructing conceptual models of groundwater flow, especially in complex geological contexts. Nevertheless, the reliability of tracer interpretation hinges on its integration into a robust geological framework. In our research, we concentrated on delineating the groundwater flow dynamics in the Innisfil Creek watershed, located in Ontario, Canada. We amalgamated extensive hydrogeological data derived from a comprehensive 3D geological model with the analysis of 61 groundwater samples, encompassing major ions, stable water isotopes, tritium, and radiocarbon. By seamlessly incorporating regional physiographic characteristics, flow pathways, and confinement attributes, we bolstered the efficiency of these tracers, resulting in several notable findings. Firstly, we identified prominent recharge and discharge zones within the watershed. Secondly, we observed the coexistence of relatively shallow and fast-flowing paths with deeper, slower-flowing channels, responsible for transporting groundwater from ancient glacial events. Thirdly, we determined that cation exchange stands as the predominant mechanism governing the geochemical evolution of contemporary water as it migrates toward confined aquifers situated at the base of the Quaternary sequence. Fourthly, we provided evidence of the mixing of modern, low-mineralized water originating from unconfined aquifer units with deep, highly mineralized water within soil–bedrock interface aquifers. These findings not only contribute significantly to the development a conceptual flow model for the sustainable management of groundwater in the Innisfil watershed, but also offer practical insights that hold relevance for analogous geological complexities encountered in other regions.
地球化学示踪剂有可能为构建地下水流动的概念模型提供有价值的见解,特别是在复杂的地质背景下。然而,示踪解释的可靠性取决于它与一个强大的地质框架的整合。在我们的研究中,我们集中描述了位于加拿大安大略省的英尼斯菲尔河流域的地下水流动动力学。我们将广泛的水文地质数据与61个地下水样本的综合三维地质模型相结合,包括主要离子、稳定水同位素、氚和放射性碳。通过无缝结合区域地理特征、流动路径和约束属性,我们提高了这些示踪剂的效率,并取得了一些显著的发现。首先,我们在流域内确定了突出的补给和排放区。其次,我们观察到相对较浅、流速较快的通道与较深、流速较慢的通道共存,这些通道负责从古冰川事件中输送地下水。第三,我们确定了阳离子交换是控制当代水地球化学演化的主要机制,因为它向第四纪层序底部的承压含水层迁移。第四,我们提供了来自无承压含水层单元的现代低矿化水与土壤-基岩界面含水层中深层高矿化水混合的证据。这些发现不仅为Innisfil流域地下水可持续管理的概念流模型的发展做出了重大贡献,而且还提供了与其他地区遇到的类似地质复杂性相关的实际见解。
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引用次数: 0
Source Attribution of Atmospheric Dust Deposition to Utah Lake 犹他湖大气粉尘的来源归属
Q2 WATER RESOURCES Pub Date : 2023-11-09 DOI: 10.3390/hydrology10110210
Justin T. Telfer, Mitchell M. Brown, Gustavious P. Williams, Kaylee B. Tanner, A. Woodruff Miller, Robert B. Sowby, Theron G. Miller
Atmospheric deposition (AD) is a significant source of nutrient loading to waterbodies around the world. However, the sources and loading rates are poorly understood for major waterbodies and even less understood for local waterbodies. Utah Lake is a eutrophic lake located in central Utah, USA, and has high-nutrient levels. Recent research has identified AD as a significant source of nutrient loading to the lake, though contributions from dust particles make up 10% of total AD. To better understand the dust AD sources, we sampled suspected source locations and collected deposition samples around the lake. We analyzed these samples using Inductively Coupled Plasma (ICP) for 25 metals to characterize their elemental fingerprints. We then compared the lake samples to the source samples to determine likely source locations. We computed spectral angle, coefficient of determination, multi-dimensional scaling, and radar plots to characterize the similarity of the samples. We found that samples from local dust sources were more similar to dust in lake AD samples than samples from distant sources. This suggests that the major source of the dust portion of AD onto Utah Lake is the local empty fields south and west of the lake, and not the farther playa and desert sources as previously suggested. Preliminary data suggest that dust AD is associated with dry, windy conditions and is episodic in nature. We show that AD from dust particles is likely a small portion of the overall AD nutrient loading on Utah Lake, with the dry and precipitation sources contributing most of the load. This case identifies AD sources to Utah Lake and provides an example of data and methods that can be used to assess similarity or perform attribution for dust, soil, and other environmental data. While we use ICP metals, any number of features can be used with these methods if normalized.
大气沉积(AD)是世界各地水体养分负荷的重要来源。然而,对主要水体的来源和加载率了解甚少,对局部水体的了解就更少了。犹他湖是一个富营养化湖泊,位于美国犹他州中部,具有很高的营养水平。最近的研究已经确定AD是湖泊营养负荷的重要来源,尽管来自尘埃颗粒的贡献占AD总量的10%。为了更好地了解沙尘AD的来源,我们对可疑的来源地点进行了采样,并收集了湖泊周围的沉积样本。我们用电感耦合等离子体(ICP)分析了25种金属样品,以表征它们的元素指纹图谱。然后,我们将湖泊样本与源样本进行比较,以确定可能的源位置。我们计算了光谱角、确定系数、多维尺度和雷达图来表征样品的相似性。我们发现来自本地沙尘源的样本比来自远处沙尘源的样本更接近AD湖样本中的沙尘。这表明AD进入犹他湖的粉尘部分的主要来源是湖泊南部和西部的当地空旷地带,而不是先前认为的更远的playa和沙漠来源。初步数据表明,沙尘AD与干燥、多风的条件有关,并且是间歇性的。研究表明,来自尘埃颗粒的AD可能只占犹他湖AD营养负荷的一小部分,干源和降水源贡献了大部分负荷。本案例确定了犹他湖的AD源,并提供了可用于评估相似性或执行粉尘、土壤和其他环境数据归因的数据和方法示例。当我们使用ICP金属时,如果规范化,这些方法可以使用任何数量的特征。
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引用次数: 0
Assessment of Nitrate in Groundwater from Diffuse Sources Considering Spatiotemporal Patterns of Hydrological Systems Using a Coupled SWAT/MODFLOW/MT3DMS Model 基于SWAT/MODFLOW/MT3DMS耦合模型的漫源地下水硝酸盐时空格局评价
Q2 WATER RESOURCES Pub Date : 2023-11-09 DOI: 10.3390/hydrology10110209
Alejandra Correa-González, Joel Hernández-Bedolla, Marco Antonio Martínez-Cinco, Sonia Tatiana Sánchez-Quispe, Mario Alberto Hernández-Hernández
In recent years, due to various anthropogenic activities, such as agriculture and livestock, the presence of nitrogen-associated contaminants has been increasing in surface- and groundwater resources. Among these, the main compounds present in groundwater are ammonia, nitrite, and nitrate. However, it is sometimes difficult to assess such effects given the scarcity or lack of information and the complexity of the system. In the current study, a methodology is proposed to assess nitrate in groundwater from diffuse sources considering spatiotemporal patterns of hydrological systems using a coupled SWAT/MODFLOW/MT3DMS model. The application of the model is carried out using a simplified simulation scheme of hydrological and agricultural systems because of the limited spatial and temporal data. The study area includes the Cuitzeo Lake basin in superficial flow form and the Morelia–Querendaro aquifer in groundwater flow form. The results within the methodology are surface runoff, groundwater levels, and nitrate concentrations present in surface- and groundwater systems. The results indicate that the historical and simulated nitrate concentrations were obtained within acceptable values of the statistical parameters and, therefore, are considered adequate.
近年来,由于各种人为活动,如农业和畜牧业,地表水和地下水资源中氮相关污染物的存在不断增加。其中,地下水中存在的主要化合物是氨、亚硝酸盐和硝酸盐。然而,由于信息稀少或缺乏以及系统的复杂性,有时很难评估这种影响。本研究提出了一种基于SWAT/MODFLOW/MT3DMS耦合水文系统时空模式的扩散源地下水硝酸盐评估方法。由于时空数据有限,模型的应用采用了简化的水文和农业系统模拟方案。研究区包括表层流形态的奎策奥湖盆地和地下水流形态的莫雷里亚-奎伦达罗含水层。该方法的结果是地表径流、地下水位以及地表和地下水系统中硝酸盐的浓度。结果表明,历史和模拟的硝酸盐浓度在统计参数的可接受值范围内获得,因此被认为是足够的。
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引用次数: 0
Machine-Learning-Based Precipitation Reconstructions: A Study on Slovenia’s Sava River Basin 基于机器学习的降水重建:斯洛文尼亚萨瓦河流域的研究
Q2 WATER RESOURCES Pub Date : 2023-11-08 DOI: 10.3390/hydrology10110207
Abel Andrés Ramírez Molina, Nejc Bezak, Glenn Tootle, Chen Wang, Jiaqi Gong
The Sava River Basin (SRB) includes six countries (Slovenia, Croatia, Bosnia and Herzegovina, Serbia, Albania, and Montenegro), with the Sava River (SR) being a major tributary of the Danube River. The SR originates in the mountains (European Alps) of Slovenia and, because of a recent Slovenian government initiative to increase clean, sustainable energy, multiple hydropower facilities have been constructed within the past ~20 years. Given the importance of this river system for varying demands, including hydropower (energy production), information about past (paleo) dry (drought) and wet (pluvial) periods would provide important information to water managers and planners. Recent research applying traditional regression techniques and methods developed skillful reconstructions of seasonal (April–May–June–July–August–September or AMJJAS) streamflow using tree-ring-based proxies. The current research intends to expand upon these recent research efforts and investigate developing reconstructions of seasonal (AMJJAS) precipitation applying novel Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) techniques. When comparing the reconstructed AMJJAS precipitation datasets, the AI/ML/DL techniques statistically outperformed traditional regression techniques. When comparing the SRB AMJJAS precipitation reconstruction developed in this research to the SRB AMJJAS streamflow reconstruction developed in previous research, the temporal variability of the two reconstructions compared favorably. However, pluvial magnitudes of extreme periods differed, while drought magnitudes of extreme periods were similar, confirming drought is likely better captured in tree-ring-based proxy reconstructions of hydrologic variables.
萨瓦河流域(SRB)包括六个国家(斯洛文尼亚,克罗地亚,波斯尼亚和黑塞哥维那,塞尔维亚,阿尔巴尼亚和黑山),萨瓦河(SR)是多瑙河的主要支流。SR起源于斯洛文尼亚的山脉(欧洲阿尔卑斯山脉),由于最近斯洛文尼亚政府倡议增加清洁,可持续能源,在过去的20年里建造了多个水电设施。考虑到这条河流系统对不同需求的重要性,包括水电(能源生产),关于过去(古)干(旱)和湿(雨)时期的信息将为水资源管理者和规划者提供重要的信息。最近的研究利用传统的回归技术和方法,利用基于树轮的代理,开发了季节性(4 - 5 - 6 - 7 - 8 - 9月或AMJJAS)流量的熟练重建。目前的研究打算扩展这些最近的研究成果,并研究应用新的人工智能(AI)、机器学习(ML)和深度学习(DL)技术重建季节性降水(AMJJAS)。对比重建的AMJJAS降水数据集,AI/ML/DL技术在统计上优于传统回归技术。将本研究开发的SRB AMJJAS降水重建与前人研究开发的SRB AMJJAS径流重建进行比较,两者的时间变率具有较好的可比性。然而,极端时期的降雨强度不同,而极端时期的干旱强度相似,这证实了基于树木年轮的水文变量替代重建可能更好地捕捉干旱。
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引用次数: 0
Assessment of Time Series Models for Mean Discharge Modeling and Forecasting in a Sub-Basin of the Paranaíba River, Brazil 巴西Paranaíba河子流域平均流量建模与预报的时间序列模型评价
Q2 WATER RESOURCES Pub Date : 2023-11-08 DOI: 10.3390/hydrology10110208
Gabriela Emiliana de Melo e Costa, Frederico Carlos M. de Menezes Filho, Fausto A. Canales, Maria Clara Fava, Abderraman R. Amorim Brandão, Rafael Pedrollo de Paes
Stochastic modeling to forecast hydrological variables under changing climatic conditions is essential for water resource management and adaptation planning. This study explores the applicability of stochastic models, specifically SARIMA and SARIMAX, to forecast monthly average river discharge in a sub-basin of the Paranaíba River near Patos de Minas, MG, Brazil. The Paranaíba River is a vital water source for the Alto Paranaíba region, serving industrial supply, drinking water effluent dilution for urban communities, agriculture, fishing, and tourism. The study evaluates the performance of SARIMA and SARIMAX models in long-term discharge modeling and forecasting, demonstrating the SARIMAX model’s superior performance in various metrics, including the Nash–Sutcliffe coefficient (NSE), the root mean square error (RMSE), and the mean absolute percentage error (MAPE). The inclusion of precipitation as a regressor variable considerably improves the forecasting accuracy, and can be attributed to the multivariate structure of the SARIMAX model. While stochastic models like SARIMAX offer valuable decision-making tools for water resource management, the study underscores the significance of employing long-term time series encompassing flood and drought periods and including model uncertainty analysis to enhance the robustness of forecasts. In this study, the SARIMAX model provides a better fit for extreme values, overestimating peaks by around 11.6% and troughs by about 5.0%, compared with the SARIMA model, which tends to underestimate peaks by an average of 6.5% and overestimate troughs by approximately 76.0%. The findings contribute to the literature on water management strategies and mitigating risks associated with extreme hydrological events.
利用随机模型预测气候变化条件下的水文变量对水资源管理和适应性规划至关重要。本研究探讨了随机模型的适用性,特别是SARIMA和SARIMAX,以预测巴西MG州帕托斯德米纳斯附近Paranaíba河子流域的月平均河流流量。Paranaíba河是阿尔托Paranaíba地区的重要水源,为工业供应、城市社区的饮用水废水稀释、农业、渔业和旅游业提供服务。研究对SARIMA和SARIMAX模型在长期流量建模和预测中的性能进行了评价,结果表明SARIMAX模型在Nash-Sutcliffe系数(NSE)、均方根误差(RMSE)和平均绝对百分比误差(MAPE)等指标上表现优异。将降水作为回归变量显著提高了预测精度,这可归因于SARIMAX模型的多元结构。虽然像SARIMAX这样的随机模型为水资源管理提供了有价值的决策工具,但该研究强调了采用包括洪涝和干旱时期在内的长期时间序列并包括模型不确定性分析以增强预测稳健性的重要性。在本研究中,SARIMAX模型提供了更好的极值拟合,峰值高估约11.6%,低谷高估约5.0%,而SARIMA模型倾向于平均低估峰值6.5%,高估低谷约76.0%。这些发现有助于水资源管理策略和减轻与极端水文事件相关的风险的文献。
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引用次数: 0
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Hydrology
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