分布式水文模型SWAT模型在新疆叶尔羌河流域的适用性研究

为定量分析SWAT模型在新疆叶尔羌流域径流模拟的适用性,以叶尔羌河卡群水文站以上集水区域为研究流域,基于卡群水文站2000-2012年水文数据,运用SWAT模型模拟了研究流域的径流量,并设定2种气候变化情景模式,定量分析不同气候变化情景模式对叶尔羌流域径流量的影响。研究结果表明:SWAT模型在叶尔羌河流域具有较好的适用性,模拟的径流深相对误差小于8%,确定性系数均达到0.75以上;在降水不变化的前提下,气温升高2℃,流域径流量增加6.28%;在气温不变前提下,降水量增加5%,流域径流量增加9.50%。研究成果对于新疆叶尔羌河流域水文模拟及预测提供参考价值。     

栅格型新安江模型在赣江流域的应用

以赣江流域峡山站以上为研究区域,利用栅格型数字高程数据,提取数字流域水系及其空间拓扑关系,在此基础上建立数字水文模型。赣江上游峡山站以上集水区域包含21198个空间分辨率为30s的栅格,采用就近移植法将降水数据及蒸发数据插值到每个栅格上,计算峡山站的径流过程。日模型中选取1978~1985年为参数率定期,1986~1987年为参数验证期,以多年径流量误差最小为目标函数。次洪模型中采用前16场洪水用于参数率定,后6场用于模拟验证,以洪水总量、洪峰流量、峰现时间按许可误差统计合格率最高和确定性系数最大为目标函数。结果显示,率定期16场洪水中14场合格,验证期6场洪水均合格,表明栅格型新安江模型模拟效果良好。     

TRMM卫星降水数据在小尺度流域的评估与应用

选取史灌河流域上游黄泥庄站以上集水区域为研究流域,以地面站点观测为基准数据,评估TRMM 3B42V7版本卫星降水数据的精度,并采用上述两种降水数据驱动栅格型新安江模型,模拟黄泥庄站日径流和月径流过程。结果表明:2001~2010年TRMM 3B42V7降水数据与雨量站数据累积量的偏差不大,仅为1.71%,但相关系数较低,采用TRMM降水数据模拟的日径流能基本再现黄泥庄站的日径流过程,但对洪峰的模拟精度较低;TRMM月降水数据精度较高,相关系数为0.96,能够较为精确地模拟黄泥庄站的月径流过程。     

一个三参数的降雨径流模型及其在我国的应用

GR3降雨径流模型属概念性集总式水文模型,具有结构简单、参数少的特点。为研究GR3降雨径流模型在我国的适用性,在长江、黄河、淮河和松花江水系,选择了7个不同尺度、不同气候条件的代表流域试用,以四种误差函数评定模拟效果。结果显示,GR3降雨径流模型在整体过程和水量平衡方面均取得较高的精度;在连续模拟中能够保持令人满意的次洪精度;比较接近的验证期与率定期精度体现了其较好的稳定性;该模型在湿润地区的表现优于半湿润地区。可以说,GR3降雨径流模型在我国有很好的应用前景。     

融合数据同化与机器学习的流域径流模拟方法

环境变化影响下流域径流的精确模拟对洪涝灾害防治与区域水资源管理都具有重要意义。在径流模拟研究中，现有机器学习模型未能充分考虑水文中间状态变量对降雨-径流过程的影响，本研究基于集合卡尔曼滤波(EnKF)更新水文状态变量，结合主成分分析(PCA)提取预报因子的主要特征，采用长短时记忆神经网络(LSTM)构建考虑水文中间变量的机器学习水文模型EnKF-PCA-LSTM。以赣江流域为例，评估EnKF-PCA-LSTM模型的径流模拟效果，同时将模拟结果与LSTM模型、物理水文模型HYMOD做对比分析。结果表明，EnKF-PCA-LSTM模型模拟径流的纳什效率系数、Kling-Gupta效率系数和对数纳什效率系数分别为0.954、0.971和0.972,比LSTM模型和HYMOD模型具有更好的模拟性能，说明考虑水文状态变量可有效提高机器学习模型的径流模拟精度及稳定性。研究成果可为流域径流模拟提供技术参考。     

改进的河道洪水演算法在大洋河流域的应用研究

对传统河道洪水演算法进行改进,引入变动态存储系数法,动态计算不同河段洪水传播时间,以大洋河沙里寨水文站以上集水区域为研究流域,将新安江模型与改进河道洪水演算法耦合模拟大洋河流域径流,并和传统河道洪水演算法径流模拟结果进行对比,此外,定量分析了不同计算时段输入对流域洪水模拟精度的影响。研究结果表明:改进的河道洪水演算方法,相比于传统洪水演算方法,模拟的径流深平均相对误差减少1.63%,确定性系数提高0.019;计算时段为1 h,相比于计算时段为1.5 h,模拟的次洪径流相对误差减少1.04%,峰现时间误差缩短0.96 h,确定性系数提高0.018。研究结果对于大洋河流域的水情预报提供参考价值。     

VIC陆面水文模型在白莲河流域径流模拟中的应用

本文从气象与水文水资源学科交叉的角度引进VIC陆面水文模型,将其应用于湖北省白莲河流域,探讨模型在中小流域降雨径流模拟中的适用性。本研究利用白莲河流域DEM、植被、土壤等数字化资料,经过模型预处理,建立了白莲河流域VIC模型框架。并进行了模型参数敏感性分析。模拟结果表明,模型基本能够反映该流域的日径流水文过程,具有一定适用性。     

滦河流域土地利用/覆被变化的水文响应

以滦河流域为研究区,利用1985和2000年土地利用数据,结合SWAT分布式水文模型定量评价了流域土地利用/覆被变化的水文效应,并分析了流域地表径流变化与主要景观类型的响应关系。结果表明:SWAT(Soil and Water Assessment Tool)模型可以较好地模拟滦河流域的月流量过程,在研究区具有较好的适用性;1985—2000年流域林地向草地和耕地的转变导致流域年均地表径流和总径流量分别增加了12.6%和5.1%;并使得流域年均地表径流变化空间差异显著,整体呈增加趋势,且主要受到林地变化的影响,而在三道河子以上集水区地表径流的变化则主要受到耕地景观的影响。合理规划土地利用格局,对于流域水资源可持续利用具有重要意义。     

SWAT模型在密赛流域的应用与比较研究

为对比分布式水文模型SWAT与典型集总式水文模型新安江模型的径流模拟能力,以钱塘江支流密赛流域为实验流域,以CRU气象数据集为气象输入资料,分别进行SWAT日、月径流模拟与验证,并与新安江模型模拟成果进行对比。结果显示SWAT模型在实验流域的月尺度径流模拟中更具优势,也表明SWAT模型在我国径流模拟中具有良好的适用性。     

滦河流域土地利用/覆被变化的水文响应

以滦河流域为研究区,利用1985和2000年土地利用数据,结合SWAT分布式水文模型定量评价了流域土地利用/覆被变化的水文效应,并分析了流域地表径流变化与主要景观类型的响应关系。结果表明:SWAT（Soil and Water Assessment Tool）模型可以较好地模拟滦河流域的月流量过程,在研究区具有较好的适用性;1985—2000年流域林地向草地和耕地的转变导致流域年均地表径流和总径流量分别增加了12.6%和5.1%;并使得流域年均地表径流变化空间差异显著,整体呈增加趋势,且主要受到林地变化的影响,而在三道河子以上集水区地表径流的变化则主要受到耕地景观的影响。合理规划土地利用格局,对于流域水资源可持续利用具有重要意义。     

基于HBV模型的太子河流域径流变化情景预估

以太子河流域为研究区域,采用HBV水文模型对流域的水文过程进行模拟,并选取RegCM4.4区域气候模式输出的平均气温和降水数据来驱动HBV水文模型,模拟逐日径流过程,分析RCP4.5排放情景下未来太子河流域径流的演变。结果表明,HBV水文模型在太子河流域模拟效果较好,率定期与验证期Nash效率系数与确定性系数均在0.60以上,模型基本模拟出了洪水对降水的响应过程。RCP4.5情景下,2021 2070年太子河流域年平均气温呈持续升温趋势,流域降水和年径流深度呈微弱减少趋势。相较于基准期,年径流深度将增多9.79%,夏季和秋季径流深度上升明显。径流分位数的变化表明,峰值极端径流和枯水极端径流均较基准期有不同程度的增多,未来太子河流域发生极端洪涝的可能性较高。     

Runoff Change in Taizihe River Basin Under Future Climate Change Based on HBV Model

Taking the Taizihe River Basin located in Liaoning Province as a study area, we applied HBV hydrological model to simulate the hydrological process of this river basin with the support of observed daily precipitation, mean temperature, hydrological data in Xiaolinzi hydrologic station, and global digital elevation model data from SRTM3, land utilization types, etc. According to the simulation results of daily runoff, the possible impact of future climate change on runoff was analyzed through forcing HBV model by RegCM4.4 dynamic downscaled climatic data. The results show that HBV model performed generally well for daily simulation of the Taizihe River Basin with Nash Sutcliffe coefficient and deterministic coefficient being all over 0.60 in the calibration period and validation period, and the response of flooding to precipitation were simulated better. This indicates the HBV model can be successfully applied to the Taizihe River Basin. Mean temperature will increase obviously with persistent rising trend by RegCM4.4 model in 2021-2070 under RCP4.5 scenario. Annual precipitation and runoff depth are expected to reduce a bit. Compared with the baseline period (1986-2005), annual runoff depth will increase by 9.79%. At the same time, the runoff depth will increase significantly in summer and autumn. The variation of runoff quantile indicates that both peak extreme runoff and dry extreme runoff will increase to different degrees than that in the baseline period. In the future, the Taizihe River Basin will be likely to experience extreme flooding.     

APHRODITE降水数据驱动的融雪径流模拟

针对流域内气象观测站点稀少和融雪径流过程的特点,利用APHRODITE降水数据进行插值,应用日有效活动温度改进度日数;依据季节性冻土受有效活动积温影响的特点,建立有效活动积温与径流系数的关系,提高模型中融雪速率和径流系数的计算精度。结合气象、水文资料和MODIS遥感积雪产品,应用改进的融雪径流模型（SRM）对开都河流域2000年与2006年融雪期的径流进行了率定和验证模拟。改进模型在率定期和验证期的模拟结果远远优于用日平均温度作为度日数的结果。结果表明,用APHRODITE降水数据及改进的度日数和径流系数作为SRM模型参数输入,能够较好模拟开都河流域融雪径流过程,大大提高模型模拟精度。     

Comparing multi-objective optimization techniques to calibrate a conceptual hydrological model using in situ runoff and daily GRACE data

Hydrological models are necessary tools for simulating the water cycle and for understanding changes in water resources. To achieve realistic model simulation results, real-world observations are used to determine model parameters within a “calibration” procedure. Optimization techniques are usually applied in the model calibration step, which assures a maximum similarity between model outputs and observations. Practical experiences of hydrological model calibration have shown that single-objective approaches might not be adequate to tune different aspects of model simulations. These limitations can be as a result of (i) using observations that do not sufficiently represent the dynamics of the water cycle, and/or (ii) due to restricted efficiency of the applied calibration techniques. To address (i), we assess how adding daily Total Water Storage (dTWS) changes derived from the Gravity Recovery And Climate Experiment (GRACE) as an extra observations, besides the traditionally used runoff data, improves calibration of a simple 4-parameter conceptual hydrological model (GR4J, in French: modèle du Génie Rural à 4 paramètres Journalier) within the Danube River Basin. As selecting a proper calibration approach (in ii) is a challenging task and might have significant influence on the quality of model simulations, for the first time, four evolutionary optimization techniques, including the Non-dominated Sorting Genetic Algorithm II (NSGA-II), the Multi-objective Particle Swarm Optimization (MPSO), the Pareto Envelope-Based Selection Algorithm II (PESA-II), and the Strength Pareto Evolutionary Algorithm II (SPEA-II) along with the Combined objective function and Genetic Algorithm (CGA) are tested to calibrate the model in (i). A number of quality measures are applied to assess cardinality, accuracy, and diversity of solutions, which include the Number of Pareto Solutions (NPS), Generation Distance (GD), Spacing (SP), and Maximum Spread (MS). Our results indicate that according to MS and SP, NSGA-II performs better than other techniques for calibrating GR4J using GRACE dTWS and in situ runoff data. Considering GD as a measure of efficiency, MPSO is found to be the best technique. CGA is found to be an efficient method, while considering the statistics of the GR4J’s 4 calibrated parameters to rank the optimization techniques. The Nash-Sutcliffe model efficiency coefficient is also used to assess the predictive power of the calibrated hydrological models, for which our results indicate satisfactory performance of the assessed calibration experiments.     

四个概念性水文模型在黑河流域上游的应用与比较分析

首先结合新安江模型、TopModel、HBV模型和Sacramento模型机理,从模型结构的土层划分、土壤水分计算、蒸散发计算、产流区不均匀性的考虑、产流机制、下渗机制等多个方面进行了理论上的比较,然后选择黑河流域上游为研究区,结合模拟结果对这四个概念性水文模型在黑河上游山区流域应用情况,从土壤水分、蒸散发、径流过程和各径流组分四个方面进行了分析比较。结果显示,概念性水文模型对黑河干流上游山区径流模拟有较好的模拟效果,但是对土壤水分、蒸散发等水文过程只能描述其变化趋势,难以定量,同时,我们还可以得出在所用四个模型中,HBV模型在黑河干流上游山区出山口的径流拟合中有和其他3个模型相当的Nash-Sutcliffe效率系数,并且在枯水期的表现也好,适用性最好。     

江西吉泰盆地卤水锂矿床地球化学特征及远景分析

吉泰盆地位于江西省中部、赣江中游,面积4550 km2.构造上属于华南褶皱系赣西南坳陷之大湖山芙蓉山隆断束与吉安凹陷的交接部位,主要沉积一套白垩系红色碎屑岩建造夹含膏盐层和卤水.基于对已知泰和县梅岗卤水锂矿地质特征、钻探成果和水系沉积物异常特征研究,认为白垩系周田组第三段、第四段碎屑岩Li最富集,Li主要还是地层同生富集引起,是本区卤水锂矿主要矿源层.结合吉泰盆地1:20万化探数据和值夏幅1:5万地球化学调查研究,圈定以梅岗锂高富集区为核心的4处远景区,在吉泰盆地赣江两岸白垩系和第四系分布8个锂富集区,表明吉泰盆地具有良好的寻找卤水锂矿远景.     

基于分布式水文模型的长江上游水资源时空变异性分析

本文首先分析了长江流域内154个气象站降水量和26个干支流水文站流量在1950～2000年期间的变化趋势。为定量分析长江上游地区降水量时空变化对水资源量的影响,构建了基于物理机理的分布式水文模型,模拟再现了天然河道条件下的水文过程。有别于传统的河道径流性水资源评价方法,本文尝试用径流深的空间变化来探讨水资源分布及演变态势。并以渠江罗渡溪水文站为个案,剖析了90年代秋季流量大幅减少的主要缘由。结果表明:受降水在时空分布上存在变异的影响,长江上游局部地区夏季径流深比率呈增加趋势,而秋季则相反;导致嘉陵江渠江水系秋季流量减少的主要原因是降雨,其次才是人为因素。     

基于径流系数的流域产流模型建立及检验

降雨径流关系因其原理简单实用在实际洪水预报中应用广泛,但一直以来是经验推算。在阐述降雨径流关系的基础上,构建了基于径流系数的流域产流模型,并确定了径流系数的计算公式。将该模型应用在伊河流域的东湾站、沙颍河流域的官寨站以及灌河鲇鱼山站等控制流域的径流预报中,结果表明,模型在3个流域的预报合格率均达到了乙级以上作业预报要求。该模型简单实用,计算步骤可行,并易于程序化,可进一步推广应用。     

SWAT模型在东江流域的应用研究

以SWAT模型为研究工具,对该模型在东江流域的3个子流域的适用性进行研究,研究表明,SWAT模型在东江流域3个子流域的适用性较好,校准期（19701975年）日径流模拟和月径流模拟的相对误差Re均在10%以内,日径流模拟的决定系数R2均在70%以上,月径流模拟的决定系数R2均在80%以上,Nash-Suttcliffe效率系数基本达到70%;验证期（19761985年及19962005年）,月径流模拟的决定系数R2和Nash-Suttcliffe效率系数均在70%以上,相对误差Re基本在±20%以内,可以满足该流域的水资源评价与规划的要求。     

Effect of climate change on water resources in the Yuanshui River Basin: a SWAT model assessment

The Yuanshui River Basin is one of the most important river basins ensuring food production and livelihoods in the Hunan and Guizhou Provinces of China. Based on digital elevation model, land use, soil, and meteorological data, the soil and water assessment tool was used to analyze the response of water resources in the basin to climate change. Specifically, the monthly runoff from the Yuanshui River Basin was simulated. Runoff measurements from the 1961–1990 series were used to calibrate model parameters, and measurements from the 1991–2010 series were used for model validation. The Nash–Sutcliffe efficiency coefficient, correlation coefficient, and water balance error were used to evaluate the simulation results; the values obtained for these parameters were 0.925, 0.929, and 2.0%, respectively, indicating that the established model can be applied successfully to runoff simulations. To evaluate the effects of climate change and human activities on runoff, 24 different climate scenarios were modeled. By comparing the model simulation results with the baseline scenario, the effects of climate change were analyzed by year, during the dry season, and during extremely dry conditions. The results showed that runoff decreased with increasing air temperature and decreasing precipitation, and that the effects of rainfall on runoff were greater than those of air temperature. Under the same baseline conditions, the effects of climate change on runoff were most pronounced during extremely dry months.