SWAT model application and prediction uncertainty analysis in the Lake Tana Basin,Ethiopia

Lake Tana Basin is of significant importance to Ethiopia concerning water resources aspects and the ecological balance of the area. Many years of mismanagement, wetland losses due to urban encroachment and population growth, and droughts are causing its rapid deterioration. The main objective of this study was to assess the performance and applicability of the soil water assessment tool (SWAT) model for prediction of streamflow in the Lake Tana Basin, so that the influence of topography, land use, soil and climatic condition on the hydrology of Lake Tana Basin can be well examined. The physically based SWAT model was calibrated and validated for four tributaries of Lake Tana. Sequential uncertainty fitting (SUFI‐2), parameter solution (ParaSol) and generalized likelihood uncertainty estimation (GLUE) calibration and uncertainty analysis methods were compared and used for the set‐up of the SWAT model. The model evaluation statistics for streamflows prediction shows that there is a good agreement between the measured and simulated flows that was verified by coefficients of determination and Nash Sutcliffe efficiency greater than 0·5. The hydrological water balance analysis of the basin indicated that baseflow is an important component of the total discharge within the study area that contributes more than the surface runoff. More than 60% of losses in the watershed are through evapotranspiration. Copyright © 2009 John Wiley & Sons, Ltd.     

Simulating streamflow in the Upper Halda Basin of southeastern Bangladesh using SWAT model

ABSTRACT

Most catchments in tropical regions are ungauged and data deficient, complicating the simulation of water quantity and quality. Yet, developing and testing hydrological models in data-poor regions is vital to support water management. Here, we used the Soil and Water Assessment Tool (SWAT) to predict stream runoff in Halda Basin in Bangladesh. While the calibrated model’s performance was satisfactory (R² = 0.80, NSE = 0.71), the model was unable to track the extreme low flow peaks due to the temporal and spatial variability of rainfall which may not be fully captured by using data from one rainfall gauging station. Groundwater delay time, baseflow alpha factor and curve number were the most sensitive parameters influencing model performance. This study improves understanding of the key processes of a catchment in a data-poor, monsoon driven, small river basin and could serve as a baseline for scenario modelling for future water management and policy framework.     

The comparative study of multi‐site uncertainty evaluation method based on SWAT model

With the recent development of distributed hydrological models, the use of multi‐site observed data to evaluate model performance is becoming more common. Distributed hydrological model have many advantages, and at the same time, it also faces the challenge to calibrate over‐do parameters. As a typical distributed hydrological model, problems also exist in Soil and Water Assessment Tool (SWAT) parameter calibration. In the paper, four different uncertainty approaches – Particle Swarm Optimization (PSO) techniques, Generalized Likelihood Uncertainty Estimation (GLUE), Sequential Uncertainty Fitting algorithm (SUFI‐2) and Parameter Solution (PARASOL) – are taken to a comparative study with the SWAT model applied in Peace River Basin, central Florida. In our study, the observed river discharge data used in SWAT model calibration were collected from the three gauging stations at the main tributary of the Peace River. Behind these approaches, there is a shared philosophy; all methods seek out many parameter set to fit the uncertainties due to the non‐uniqueness in model parameter evaluation. On the basis of the statistical results of four uncertainty methods, difficulty level of each method, the number of runs and theoretical basis, the reasons that affected the accuracy of simulation were analysed and compared. Furthermore, for the four uncertainty method with SWAT model in the study area, the pairwise correlation between parameters and the distributions of model fit summary statistics computed from the sampling over the behavioural parameter and the entire model calibration parameter feasible spaces were identified and examined. It provided additional insight into the relative identifiability of the four uncertainty methods Copyright © 2014 John Wiley & Sons, Ltd.     

Parameter identification and uncertainty analysis for simulating streamflow in a river basin of Eastern India

Uncertainty is inherent in modelling studies. However, the quantification of uncertainties associated with a model is a challenging task, and hence, such studies are somewhat limited. As distributed or semi‐distributed hydrological models are being increasingly used these days to simulate hydrological processes, it is vital that these models should be equipped with robust calibration and uncertainty analysis techniques. The goal of the present study was to calibrate and validate the Soil and Water Assessment Tool (SWAT) model for simulating streamflow in a river basin of Eastern India, and to evaluate the performance of salient optimization techniques in quantifying uncertainties. The SWAT model for the study basin was developed and calibrated using Parameter Solution (ParaSol), Sequential Uncertainty Fitting Algorithm (SUFI‐2) and Generalized Likelihood Uncertainty Estimation (GLUE) optimization techniques. The daily observed streamflow data from 1998 to 2003 were used for model calibration, and those for 2004–2005 were used for model validation. Modelling results indicated that all the three techniques invariably yield better results for the monthly time step than for the daily time step during both calibration and validation. The model performances for the daily streamflow simulation using ParaSol and SUFI‐2 during calibration are reasonably good with a Nash–Sutcliffe efficiency and mean absolute error (MAE) of 0.88 and 9.70 m³/s for ParaSol, and 0.86 and 10.07 m³/s for SUFI‐2, respectively. The simulation results of GLUE revealed that the model simulates daily streamflow during calibration with the highest accuracy in the case of GLUE (R² = 0.88, MAE = 9.56 m³/s and root mean square error = 19.70 m³/s). The results of uncertainty analyses by SUFI‐2 and GLUE were compared in terms of parameter uncertainty. It was found that SUFI‐2 is capable of estimating uncertainties in complex hydrological models like SWAT, but it warrants sound knowledge of the parameters and their effects on the model output. On the other hand, GLUE predicts more reliable uncertainty ranges (R‐factor = 0.52 for daily calibration and 0.48 for validation) compared to SUFI‐2 (R‐factor = 0.59 for daily calibration and 0.55 for validation), though it is computationally demanding. Although both SUFI‐2 and GLUE appear to be promising techniques for the uncertainty analysis of modelling results, more and more studies in this direction are required under varying agro‐climatic conditions for assessing their generic capability. Copyright © 2015 John Wiley & Sons, Ltd.     

Parameter and rating curve uncertainty propagation analysis of the SWAT model for two small Mediterranean catchments

Abstract

The SWAT model was tested to simulate the streamflow of two small Mediterranean catchments (the Vène and the Pallas) in southern France. Model calibration and prediction uncertainty were assessed simultaneously by using three different techniques (SUFI-2, GLUE and ParaSol). Initially, a sensitivity analysis was conducted using the LH-OAT method. Subsequent sensitive parameter calibration and SWAT prediction uncertainty were analysed by considering, firstly, deterministic discharge data (assuming no uncertainty in discharge data) and secondly, uncertainty in discharge data through the development of a methodology that accounts explicitly for error in the rating curve (the stage?discharge relationship). To efficiently compare the different uncertainty methods and the effect of the uncertainty of the rating curve on model prediction uncertainty, common criteria were set for the likelihood function, the threshold value and the number of simulations. The results show that model prediction uncertainty is not only case-study specific, but also depends on the selected uncertainty analysis technique. It was also found that the 95% model prediction uncertainty interval is wider and more successful at encompassing the observations when uncertainty in the discharge data is considered explicitly. The latter source of uncertainty adds additional uncertainty to the total model prediction uncertainty.

Editor D. Koutsoyiannis; Associate editor D. Gerten

Citation Sellami, H., La Jeunesse, I., Benabdallah, S., and Vanclooster, M., 2013. Parameter and rating curve uncertainty propagation analysis of the SWAT model for two small Mediterranean watersheds. Hydrological Sciences Journal, 58 (8), 1635?1657.     

Simulating spatiotemporal variability of blue and green water resources availability with uncertainty analysis

Due to rapid socioeconomic development, continuous population growth and urbanization, the world is facing a severe shortage of fresh water, particularly in arid and semi‐arid regions. A lack of water will put pressure on agricultural production, water pollution, as well as eco‐environmental degradation. Traditional water resources assessment mainly focused on blue water, ignoring green water. Therefore, analysis of spatiotemporal distribution of blue and green water resources in arid and semi‐arid regions is of great significance for water resources planning and management, especially for harmonizing agricultural water use and eco‐environmental water requirements. This study applied the Soil and Water Assessment Tool (SWAT) model and the Sequential Uncertainty Fitting algorithm (SUFI‐2) to calibrate and validate the SWAT model based on river discharges in the Wei River, the largest tributary of the Yellow River in China. Uncertainty analysis was also performed to quantify the blue and green water resources availability at different spatial scales. The results showed that most parts of the Wei River basin (WRB) experienced a decrease in blue water resources during the recent 50 years with a minimum value in the 1990s. The decrease is particularly significant in the most southern part of the WRB (the Guanzhong Plain), one of the most important grain production bases in China. Variations of green water flow and green water storage were relatively small both on spatial and temporal dimensions. This study provides strategic information for optimal utilization of water resources in arid and semi‐arid river basin. Copyright © 2014 John Wiley & Sons, Ltd.     

基于Copula函数的鄱阳湖水系径流丰枯遭遇多维分析

鄱阳湖流域5大水系来水变化与湖区水文极值事件有密切关系,研究径流变化特征与丰枯遭遇规律对区域防洪抗旱有重要意义.本文运用Copula函数构建了鄱阳湖水系多维径流联合分布模型,采用特枯、偏枯、平水、偏丰和特丰的径流丰枯分类,定量研究了鄱阳湖5大水系丰枯遭遇的问题,探讨了多维丰枯遭遇同步联合概率的变化特征.结果表明：鄱阳湖水系河流之间的径流具有较高的相关性,Gaussian Copula函数能较好地模拟二维至五维的径流联合分布.多条河流的丰枯遭遇随着维数的增加,丰枯组合增加,丰枯同步的联合概率明显下降,且丰枯同步的最大联合概率趋向于丰枯两端.对于相同的概率区间,非汛期径流的丰枯同步联合概率明显大于年径流和汛期径流,而年径流和汛期径流之间的丰枯同步联合概率差别较小.同处于流域北部或南部或相邻的河流之间的组合,其同步联合概率相较其他组合大,而南、北河流组合的同步联合概率相对较小.该研究可为流域水资源管理及水旱灾害预防提供科学依据.     

Calibration and uncertainty analysis of the SWAT model using Genetic Algorithms and Bayesian Model Averaging

In this paper, the Genetic Algorithms (GA) and Bayesian Model Averaging (BMA) were used to simultaneously conduct calibration and uncertainty analysis for the Soil and Water Assessment Tool (SWAT). In this combined method, several SWAT models with different structures are first selected; next GA is used to calibrate each model using observed streamflow data; finally, BMA is applied to combine the ensemble predictions and provide uncertainty interval estimation. This method was tested in two contrasting basins, the Little River Experimental Basin in Georgia, USA, and the Yellow River Headwater Basin in China. The results obtained in the two case studies show that this combined method can provide deterministic predictions better than or comparable to the best calibrated model using GA. The 66.7% and 90% uncertainty intervals estimated by this method were analyzed. The differences between the percentage of coverage of observations and the corresponding expected coverage percentage are within 10% for both calibration and validation periods in these two test basins. This combined methodology provides a practical and flexible tool to attain reliable deterministic simulation and uncertainty analysis of SWAT.     

鄱阳湖流域水文极值演变特征、成因与影响

选用11种概率分布函数,系统分析了鄱阳湖流域"五河"的6个水文站年最大径流量与连续3d、7d最大平均日流量,函数参数以及拟合优度分别由线性矩法与柯尔莫哥洛夫-斯米尔诺夫方法检验,选出最适合该区流量极值分布函数.在此基础上,对引起该流域水文极值变化的原因及其影响作了有益的探讨.结果表明:(1)韦克比分布是用于研究都阳湖流...     

Quantitative assessment of the contribution of climate variability and human activity to streamflow alteration in Dongting Lake,China

Climate variability and human activity were regarded as two contributors to streamflow alteration. However, the contributions of the two factors were still unclear in Dongting Lake. Therefore, it was crucial to quantify the relative impact of climate variability and human activity on streamflow alteration. The time series (1961–2010) was divided into three periods, namely, natural period (1961–1980), change period I (1981–2002) and change period II (2003–2010). Sensitivity analysis based on Budyko‐type equations was applied to reveal the contributions of climate variability and human activity in those two change periods, respectively. The results showed that during the change period I, climate variability was the main factor responsible for streamflow alteration in most parts of Dongting Lake, accounting for 60.07–67.27%. However, the impact of climate variability was slightly smaller than that of human activity in West Dongting Lake (the former accounting for 43.20% while the latter accounting for 56.80%). For the change period II, human activity was the dominate factor for streamflow alteration, accounting for 58.89–78.33%. The impact of climate variability gradually decreased while the impact of human activity gradually increased. Along with the intensification of the human activity, the impact of it became more dominant. The results could provide a reference for water resources planning and management decisions. Under the condition of uncontrollable climatic factor, effective measures should be put forward in controlling human activity, such as reservoir/dam operation, closed management of protected area and so on. Besides, it is essential to study the impact of climate variability on future water resources and water resource management under different climate change scenarios. Copyright © 2016 John Wiley & Sons, Ltd.     

Analyses of the impact of climate change on water resources components,drought and wheat yield in semiarid regions: Karkheh River Basin in Iran

Water resources availability in the semiarid regions of Iran has experienced severe reduction because of increasing water use and lengthening of dry periods. To better manage this resource, we investigated the impact of climate change on water resources and wheat yield in the Karkheh River Basin (KRB) in the semiarid region of Iran. Future climate scenarios for 2020–2040 were generated from the Canadian Global Coupled Model for scenarios A1B, B1 and A2. We constructed a hydrological model of KRB using the Soil and Water Assessment Tool to project water resources availability. Blue and green water components were modeled with uncertainty ranges for both historic and future data. The Sequential Uncertainty Fitting Version 2 was used with parallel processing option to calibrate the model based on river discharge and wheat yield. Furthermore, a newly developed program called critical continuous day calculator was used to determine the frequency and length of critical periods for precipitation, maximum temperature and soil moisture. We found that in the northern part of KRB, freshwater availability will increase from 1716 to 2670 m³/capita/year despite an increase of 28% in the population in 2025 in the B1 scenario. In the southern part, where much of the agricultural lands are located, the freshwater availability will on the average decrease by 44%. The long‐term average irrigated wheat yield, however, will increase in the south by 1.2%–21% in different subbasins; but for rain‐fed wheat, this variation is from ?4% to 38%. The results of critical continuous day calculator showed an increase of up to 25% in both frequency and length of dry periods in south Karkheh, whereas increasing flood events could be expected in the northern and western parts of the region. In general, there is variability in the impact of climate change in the region where some areas will experience net negative whereas other areas will experience a net positive impact. Copyright © 2013 John Wiley & Sons, Ltd.     

滇池不同湖区浮游动物群落稳定性及其驱动因子分析

为了揭示滇池不同湖区浮游动物群落稳定性及其驱动因子,于2020年对滇池草海、大泊口、外海3个具有一定空间分隔的区域,按季度进行4次采样调查。结果表明,大泊口区域的溶解氧、透明度指标显著高于外海,总氮、总磷、悬浮物、叶绿素a和化学需氧量等指标浓度显著低于外海,草海理化因子浓度介于大泊口与外海之间。研究期间3个区域共鉴定出浮游动物41属(枝角类12属、桡足类8属、轮虫21属),轮虫种类和密度均占较大比例。浮游动物年平均密度大泊口(7771.3 ind./L)>草海(2901.1 ind./L)>外海(634.8 ind./L);年平均生物量草海(3.72 mg/L)>大泊口(2.15 mg/L)>外海(2.09 mg/L)。非参数多元方差分析(PERMANOVA)与相似性百分比分析(SIMPER)结果表明,滇池3个区域间浮游动物群落结构差异极显著,导致大泊口与草海、外海群落结构呈极显著差异的属种为轮虫类群的种类,导致草海与外海群落结构呈极显著差异的属种为枝角类和轮虫类群的种类。此外,浮游动物群落稳定性与物种多样性呈显著的正相关关系,且经过生态修复后水质有所改善的湖区...     

Simultaneous calibration of surface flow and baseflow simulations: a revisit of the SWAT model calibration framework

Accurate analysis of water flow pathways from rainfall to streams is critical for simulating water use, climate change impact, and contaminants transport. In this study, we developed a new scheme to simultaneously calibrate surface flow (SF) and baseflow (BF) simulations of soil and water assessment tool (SWAT) by combing evolutionary multi‐objective optimization (EMO) and BF separation techniques. The application of this scheme demonstrated pronounced trade‐off of SWAT's performance on SF and BF simulations. The simulated major water fluxes and storages variables (e.g. soil moisture, evapotranspiration, and groundwater) using the multiple parameters from EMO span wide ranges. Uncertainty analysis was conducted by Bayesian model averaging of the Pareto optimal solutions. The 90% confidence interval (CI) estimated using all streamflows substantially overestimate the uncertainty of low flows on BF days while underestimating the uncertainty of high flows on SF days. Despite using statistical criteria calculated based on streamflow for model selection, it is important to conduct diagnostic analysis of the agreement of SWAT behaviour and actual watershed dynamics. The new calibration technique can serve as a useful tool to explore the trade‐off between SF and BF simulations and provide candidates for further diagnostic assessment and model identification. Copyright © 2011 John Wiley & Sons, Ltd.     

Assessing the performance and uncertainty analysis of the SWAT and RBNN models for simulation of sediment yield in the Nagwa watershed,India

Abstract

The process-based Soil and Water Assessment Tool (SWAT) model and the data-driven radial basis neural network (RBNN) model were evaluated for simulating sediment load for the Nagwa watershed in Jharkhand, India, where soil erosion is a severe problem. The SWAT model calibration and uncertainty analysis were performed with the Sequential Uncertainty Fitting algorithm version 2 and the bootstrap technique was applied on the RBNN model to analyse uncertainty in model output. The percentage of data bracketed by the 95% prediction uncertainty (95PPU) and the r factor were the two measures used to assess the goodness of calibration. Comparison of the results of the two models shows that the value of r factor (r = 0.41) in the RBNN model is less than that of SWAT model (r = 0.79), which means there is a wider prediction interval for the SWAT model results. More values of observed sediment yield were bracketed by the 95PPU in the RBNN model. Thus, the RBNN model estimates the sediment yield values more accurately and with less uncertainty.

Editor D. Koutsoyiannis; Associate editor H. Aksoy

Citation Singh, A., Imtiyaz, M., Isaac, R.K., and Denis, D.M., 2014. Assessing the performance and uncertainty analysis of the SWAT and RBNN models for simulation of sediment yield in the Nagwa watershed, India. Hydrological Sciences Journal, 59 (2), 351–364.     

Non‐point source pollution modelling using Soil and Water Assessment Tool and its parameter sensitivity analysis in Xin'anjiang catchment,China

Non‐point source pollution is a key issue in integrated river basin management around the world and has resulted in water contamination, aquatic ecology deterioration and eutrophication. Xin'anjiang catchment is the key drinking water source area for Hangzhou City, China. A promising model (Soil and Water Assessment Tool) was applied to assess the non‐point source pollution and its effect on drinking water. Sensitivity analysis of model parameters was carried out using the Sequential Uncertainty Domain Parameter Fitting 2 sensitivity technique. Water discharge, sediment, total nitrogen and total phosphorus load processes from 2000 to 2010 were simulated, and the spatial distributions of non‐point source pollutants were evaluated at the catchment and administrative country levels. The results show that the hydrological parameters of the Soil and Water Assessment Tool were dominantly sensitive for non‐point source pollution simulation, including CN2, RCHRG_DP, ALPHA_BF, SOL_AWC, ESCO and SOL_K and the characteristic parameters of sub‐basins (viz. HRU_SLP and SLSUBBSN). Also, water quality parameters (viz. CH_EROD, NPERCO, RSDCO and PPERCO, PHOSKD, etc.) have a significant effect on nutrients. The model performance was very satisfactory, especially for runoff, sediment and total phosphorus simulation. The non‐point source pollutant load increased from 2001 to 2010 in the whole catchment. Total nitrogen load increased from 3428 tons (0.59 ton km^?2) to 7315 tons (1.25 ton km^?2), and total phosphorus load increased from 299 tons (0.05 ton km^?2) to 867 tons (0.15 ton km^?2). The contribution of rice land was the largest, accounting for nearly 95%, followed by tea garden (3.56%), winter wheat (1.37%), forest (0.07%) and grassland (0.02%). Moreover, She County and Xiuning County contributed more than half of the non‐point source pollutants. This study was expected to provide a method and reference for non‐point source pollution quantification and to support water quality management implementation in China. Copyright © 2012 John Wiley & Sons, Ltd.     

Sensitivity and uncertainty analysis of mesoscale model downscaled hydro‐meteorological variables for discharge prediction

Precipitation and Reference Evapotranspiration (ETo) are the most important variables for rainfall–runoff modelling. However, it is not always possible to get access to them from ground‐based measurements, particularly in ungauged catchments. This study explores the performance of rainfall and ETo data from the global European Centre for Medium Range Weather Forecasts (ECMWF) ERA interim reanalysis data for the discharge prediction. The Weather Research and Forecasting (WRF) mesoscale model coupled with the NOAH Land Surface Model is used for the retrieval of hydro‐meteorological variables by downscaling ECMWF datasets. The conceptual Probability Distribution Model (PDM) is chosen for this study for the discharge prediction. The input data and model parameter sensitivity analysis and uncertainty estimations are taken into account for the PDM calibration and prediction in the case study catchment in England following the Generalized Likelihood Uncertainty Estimation approach. The goodness of calibration and prediction uncertainty is judged on the basis of the p‐factor (observations bracketed by the prediction uncertainty) and the r‐factor (achievement of small uncertainty band). The overall analysis suggests that the uncertainty estimates using WRF downscaled ETo have slightly smaller p and r values (p= 0.65; r= 0.58) as compared to ground‐based observation datasets (p= 0.71; r= 0.65) during the validation and hence promising for discharge prediction. On the contrary, WRF precipitation has the worst performance, and further research is needed for its improvement (p= 0.04; r= 0.10). Copyright © 2013 John Wiley & Sons, Ltd.     

How to improve the representation of hydrological processes in SWAT for a lowland catchment – temporal analysis of parameter sensitivity and model performance

Model diagnostic analyses help to improve the understanding of hydrological processes and their representation in hydrological models. A detailed temporal analysis detects periods of poor model performance and model components with potential for model improvements, which cannot be found by analysing the whole discharge time series. In this study, we aim to improve the understanding of hydrological processes by investigating the temporal dynamics of parameter sensitivity and of model performance for the Soil and Water Assessment Tool model applied to the Treene lowland catchment in Northern Germany. The temporal analysis shows that the parameter sensitivity varies temporally with high sensitivity for three groundwater parameters (groundwater time delay, baseflow recession constant and aquifer fraction coefficient) and one evaporation parameter (soil evaporation compensation factor). Whereas the soil evaporation compensation factor dominates in baseflow and resaturation periods, groundwater time delay, baseflow recession constant and aquifer fraction coefficient are dominant in the peak and recession phases. The temporal analysis of model performance identifies three clusters with different model performances, which can be related to different phases of the hydrograph. The lowest performance, when comparing six performance measures, is detected for the baseflow cluster. A spatially distributed analysis for six hydrological stations within the Treene catchment shows similar results for all stations. The linkage of periods with poor model performance to the dominant model components in these phases and with the related hydrological processes shows that the groundwater module has the highest potential for improvement. This temporal diagnostic analysis enhances the understanding of the Soil and Water Assessment Tool model and of the dominant hydrological processes in the lowland catchment. Copyright © 2013 John Wiley & Sons, Ltd.     

长江中下游平原升金湖流域硝酸盐来源解析及其不确定性

考虑流域地理特征的空间分异,以升金湖流域人口/农业集约区大渡口(DDK)与森林子流域唐田河(TTH)为研究区,利用贝叶斯同位素混合模型分别解析这2个子流域硝酸盐来源的贡献率,并分析其不确定性. 研究表明:(1)地下水中,DDK?TTH硝酸盐均主要来源于粪便/污水,贡献率可达65%以上,粪便/污水通过土壤下渗导致地下水硝...     

柴达木盆地尕斯库勒盐湖地表水-地下水的转化与铀的补给通量

流域范围内地表水和地下水转化对盐湖成盐元素的运移和富集具有十分重要的意义.本文通过尕斯库勒盐湖盆地内流域水体的水化学和B同位素特征识别了地表水和地下水之间的定量转化关系,在此基础上估算了流域中铀的补给通量.结果表明,流域水体中离子的分异除了蒸发浓缩作用之外,还受重力分异及掺杂作用的影响;上游库拉木勒克萨伊河和阿特阿特坎河水体在出山口附近转入地下并在中游补给地表水和地下水,其补给率分别占48.8%和51.2%,年均补给量分别为1.08×108和1.13×108m3/a;在中游至尾闾盐湖段,阿拉尔河和侧向补给对盐湖卤水的补给率占55.2%,深部水体的补给占44.8%;至少从5.7 ka以来,上游水体对盐湖卤水中铀的补给通量为4.11×103t,在湖积平原黏土沉积带以及祁漫塔格山前局部还原带可能具有较大规模的铀矿.研究结果有助于建立盐湖盆地水循环模式、揭示卤水资源形成机制;同时为尕斯库勒盐湖盆地水资源的高效利用和寻找铀矿提供理论依据和技术支持.