油田压裂井地电法双参数联合监测技术与仪器研究

目前世界上水力压裂技术是老油田增产和低渗透油气田开发所应用最为广泛、最为有效的技术措施,油气储层裂缝分布规律监测对于油田勘探开发具有重要意义.本文利用压裂液在地层中的低阻特性与极化特性,基于井地电阻率法与激发极化法联合,根据位场理论镜像原理,采用三维有限差分,计算了多种压裂模型的地表传导电位与极化电位;通过非等权值的数据融合算法,计算了地表双参数异常,仿真数据的研究结果表明,双参数融合技术在异常提取方面具有明显优势.在此基础上,基于双波大功率联合发射技术、时分复用低噪声接收技术,研制了井地电法双参数联合监测仪器系统,共模抑制比达110 dB,有效地提取了微弱异常信号.通过陕西省富县华北局油田的压裂野外联合监测试验,表明了井地电法双参数联合监测仪器系统在水力压裂裂缝监测中具有较好的监测效果和较高的分辨率,解决了在低电阻率储层压裂或深井压裂情况下监测困难以及单一方法的监测结果多解性等问题,实现对油田水力压裂裂缝的实时监测.     

Modification of the SWAT model to simulate regional groundwater flow using a multicell aquifer

The soil and water assessment tool (SWAT) has been widely used and thoroughly tested in many places in the world. The application of the SWAT model has pointed out that 2 of the major weaknesses of SWAT are related to the nonspatial reference of the hydrologic response unit concept and to the simplified groundwater concept, which contribute to its low performance in baseflow simulation and its inability to simulate regional groundwater flow. This study modified the groundwater module of SWAT to overcome the above limitations. The modified groundwater module has 2 aquifers. The local aquifer, which is the shallow aquifer in the original SWAT, represents a local groundwater flow system. The regional aquifer, which replaces the deep aquifer of the original SWAT, represents intermediate and regional groundwater flow systems. Groundwater recharge is partitioned into local and regional aquifer recharges. The regional aquifer is represented by a multicell aquifer (MCA) model. The regional aquifer is discretized into cells using the Thiessen polygon method, where centres of the cells are locations of groundwater observation wells. Groundwater flow between cells is modelled using Darcy's law. Return flow from cell to stream is conceptualized using a non‐linear storage–discharge relationship. The SWAT model with the modified aquifer module, the so‐called SWAT‐MCA, was tested in 2 basins (Wipperau and Neetze) with porous aquifers in a lowland area in Lower Saxony, Germany. Results from the Wipperau basin show that the SWAT‐MCA model is able (a) to simulate baseflow in a lowland area (where baseflow is a dominant source of streamflow) better than the original model and (b) to simulate regional groundwater flow, shown by the simulated groundwater levels in cells, quite well.     

Multi-objective autocalibration of SWAT model for improved low flow performance for a small snowfed catchment

ABSTRACT

A reliable modelling framework needs to ensure that the model is simulating reality with limited uncertainty, thus enhancing its predictive ability. In the literature, hydrological model assessment using one or more metrics is reported to be inadequate when the river flow regime is required to be reproduced comprehensively. This research is aimed to: (a) calibrate the Soil and Water Assessment Tool (SWAT) based on the concept of multi-objective optimization by applying the Borg multi-objective evolutionary algorithm (MOEA); (b) apply hydrological signatures as objective functions; and (c) adopt a multi-metric approach for model evaluation. The SWAT model was coupled with a relatively newer and powerful Borg MOEA. The inclusion of hydrological signatures as objective functions along with the conventional statistical functions assisted in improving the performance for low flows by 135% in terms of volume efficiency and 65% for flow time series simulation.     

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.     

The effect of land cover change on duration and severity of high and low flows

Land cover has been increasingly recognized as an important factor affecting hydrologic processes at the basin and regional level. Therefore, improved understanding of how land cover change affects hydrologic systems is needed for better management of water resources. The objective of this study is to investigate the effects of land cover change on the duration and severity of high and low flows by using the Soil Water Assessment Tool model, Bayesian model averaging and copulas. Two basins dominated by different land cover in the Ohio River basin are used as study area in this study. Two historic land covers from the 1950s and 1990s are considered as input to the Soil Water Assessment Tool model, thereby investigating the hydrologic high and low flow response of different land cover conditions of these two basins. The relationships between the duration and severity of both low and high flow are defined by applying the copula method; changes in the frequency of the duration and severity are investigated. The results show that land cover changes affect both the duration and severity of both high and low flows. An increase in forest area leads to a decrease in the duration and severity during both high and low flows, but its impact is highest during extreme flows. The results also show that the land cover changes have had significant influences on changes in the joint return periods of duration and severity of low and high flows. While this study sheds light on the role of land cover change on severity and duration of high and low flow conditions, more studies using various land cover conditions and climate types are required in order to draw more reliable conclusions in the future. Copyright © 2016 John Wiley & Sons, Ltd.     

Estimation of irrigation return flow on monthly time resolution using SWAT model under limited data availability

ABSTRACT

This study is an assessment of the return flow ratio of an irrigation abstraction using the flow records of a downstream stream-gauging station, with the example of the Kozluk scheme irrigated by diverted water from Garzan Creek flowing through the southeastern region of Turkey. In the planning reports of the major dam projects of the region, an unverified return ratio was assumed in eliminating the influence of this irrigation on the flow measurements of Garzan Creek. The correctness of this assumed return ratio is evaluated by analysing the monthly streamflow measurements of the Besiri station through a Soil and Water Assessment Tool (SWAT) model constructed with the coarse-scale topography, land use and soil data from open source databases. The results show the necessity of irrigation project-based return flow analyses using regional fine-scale datasets, instead of rule-of-thumb assumptions, to determine the effects of irrigation activities on flow regimes more accurately.     

Estimation of instantaneous peak flows from maximum mean daily flows using the HBV hydrological model

The record length and quality of instantaneous peak flows (IPFs) have a great influence on flood design, but these high resolution flow data are not always available. The primary aim of this study is to compare different strategies to derive frequency distributions of IPFs using the Hydrologiska Byråns Vattenbalansavdelning (HBV) hydrologic model. The model is operated on a daily and an hourly time step for 18 catchments in the Aller‐Leine basin, Germany. Subsequently, general extreme value (GEV) distributions are fitted to the simulated annual series of daily and hourly extreme flows. The resulting maximum mean daily flow (MDF) quantiles from daily simulations are transferred into IPF quantiles using a multiple regression model, which enables a direct comparison with the simulated hourly quantiles. As long climate records with a high temporal resolution are not available, the hourly simulations require a disaggregation of the daily rainfall. Additionally, two calibrations strategies are applied: (1) a calibration on flow statistics; (2) a calibration on hydrographs. The results show that: (1) the multiple regression model is capable of predicting IPFs with the simulated MDFs; (2) both daily simulations with post‐correction of flows and hourly simulations with pre‐processing of precipitation enable a reasonable estimation of IPFs; (3) the best results are achieved using disaggregated rainfall for hourly modelling with calibration on flow statistics; and (4) if the IPF observations are not sufficient for model calibration on flow statistics, the transfer of MDFs via multiple regressions is a good alternative for estimating IPFs. Copyright © 2015 John Wiley & Sons, Ltd.     

Trends in timing of low stream flows in Canada: impact of autocorrelation and long‐term persistence

The annual timing of river flows might indicate changes that are climate related. In this study, trends in timing of low flows for the Reference Hydrometric Basin Network were investigated under three different hypotheses namely: independence, short‐term persistence (STP) and long‐term persistence (LTP). Both summer and winter time series were characterized with scaling behaviour providing strong evidence of LTP. The Mann–Kendall trend test was modified to account for STP and LTP, and used to detect trends in timing of low flows. It was found that considering STP and LTP resulted in a significant decrease in the number of detected trends. Numerical analysis showed that the timing of summer 7‐day low flows exhibited significant trends in 16, 9 and 7% of stations under independence, STP and LTP assumptions, respectively. Timing of summer low flow shifted toward later dates in western Canada, whereas the majority of stations in the east half of the country (except Atlantic Provinces) experienced a shift toward earlier dates. Timing of winter low flow experienced significant trends in 20, 12, and 6% of stations under independence, STP and LTP assumptions, respectively. Shift in timing of winter low flow toward earlier dates was dominant all over the country where it shifted toward earlier dates in up to 3/4 of time series with significant trends. There are local patterns of upward significant/insignificant trends in southeast, southwest and northern Canada. This study shows that timing of low flows in Canada is time dependent; however, addressing the full complexity of memory properties (i.e. short term vs long term) of a natural process is beyond the scope of this study. Copyright © 2009 John Wiley & Sons, Ltd.     

Relationships between snowpack,low flows and stream temperature in mountain watersheds of the US west coast

Water temperatures in mountain streams are likely to rise under future climate change, with negative impacts on ecosystems and water quality. However, it is difficult to predict which streams are most vulnerable due to sparse historical records of mountain stream temperatures as well as complex interactions between snowpack, groundwater, streamflow and water temperature. Minimum flow volumes are a potentially useful proxy for stream temperature, since daily streamflow records are much more common. We confirmed that there is a strong inverse relationship between annual low flows and peak water temperature using observed data from unimpaired streams throughout the montane regions of the United States' west coast. We then used linear models to explore the relationships between snowpack, potential evapotranspiration and other climate-related variables with annual low flow volumes and peak water temperatures. We also incorporated previous years' flow volumes into these models to account for groundwater carryover from year to year. We found that annual peak snowpack water storage is a strong predictor of summer low flows in the more arid watersheds studied. This relationship is mediated by atmospheric water demand and carryover subsurface water storage from previous years, such that multi-year droughts with high evapotranspiration lead to especially low flow volumes. We conclude that watershed management to help retain snow and increase baseflows may help counteract some of the streamflow temperature rises expected from a warming climate, especially in arid watersheds.     

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.     

Impacts of land use and land cover changes on hydrological processes and sediment yield determined using the SWAT model

Land use and land cover (LULC) changes strongly affect local hydrology and sediment yields.The current study focused on a basin in the Brazilian Amazon and had the following three objectives:(1) to perform an effective diagnosis of flow and sediment yield,(2) to evaluate the impacts of LULC changes over the last 40 years on the hydro-sedimentological variables,and (3) to investigate the impacts of the possible trends or breaking points in the flow,surface runoff,and sediment yield series.The Soi...     

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.     

Regional analysis of low flow using L-moments for Dongjiang basin,South China

Abstract

Dongjiang water has been the key source of water supplies for Hong Kong and its neighbouring cities in the Pearl River Delta in South China since the mid-1960s. Rapid economic development and population growth in this region have caused serious concerns over the adequacy of the quantity and quality of water withdrawn from the Dongjiang River in the future. Information on the magnitude and frequency of low flows in the basin is needed for planning of water resources at present and in the near future. The L-moment method is used to analyse the regional frequency of low flows, since recent studies have shown that it is superior to other methods that have been used previously, and is now being adopted by many organizations worldwide. In this study, basin-wide analysis of low flows is conducted for Dongjiang basin using five distributions: generalized logistic, generalized extreme value, lognormal, Pearson type III and generalized Pareto. Each of these has three parameters estimated by the L-moment method. The discordancy index and homogeneity testing show that 14 out of the 16 study sites belong to a homogenous region; these are used for further analysis. Based on the L-moment ratios diagram, the Hosking and Wallis goodness-of-fit statistical criterion and the L-kurtosis criterion, the three-parameter lognormal distribution is identified as the most appropriate distribution for the homogeneous study region. The regional low-flow estimates for each return period are obtained using the index flood procedure. Examination of the observed and simulated low flows by regional frequency analysis shows a good agreement in general, and the results may satisfy practical application. Furthermore, the regional low-flow relationship between mean annual 7-day low flows and basin area is developed using linear regression, providing a simple and effective method for estimation of low flows of desired return periods for ungauged catchments.     

Modelling the impact of recent land‐cover changes on the stream flows in northeastern Puerto Rico

We investigated the influence of recent and future land‐cover changes on stream flow of a watershed northeastern Puerto Rico using hydrological modeling and simulation analysis. Monthly and average annual stream flows were compared between an agricultural period (1973–1980) and an urbanized/reforested period (1988–1995) using the revised Generalized Watershed Loading Function model. Our validated results show that a smaller proportion of rainfall became stream flows in the urbanized/forested period compared with the agricultural period, apparently because of reforestation. Sensitivity analysis of the model showed that evapotranspiration, precipitation, and curve number were the most significant factors influencing stream flow. Simulations of projected land‐cover scenarios indicate that annual stream flows would increase by 9·6% in a total urbanization scenario, decrease by 3·6% in a total reforestation scenario, and decrease by 1·1% if both reforestation and urbanization continue at their current rates to 2020. An imposed hurricane event that was similar in scale to the largest recent event on the three land‐cover scenarios would increase the daily stream flow by 62·1%, 68·4% and 67·1% respectively. Owing to the environmental setting of eastern Puerto Rico, where sea breezes caused by temperature differences between land surface and the ocean dominate the local climate, we suggest that managing local land‐cover changes can have important consequences for water management. Copyright © 2007 John Wiley & Sons, Ltd.     

The impacts of climate change on local hydrology and low flow frequency in the Geum River Basin,Korea

The climate sensitive analysis of potential climate change on streamflow has been conducted using a hydrologic model to identify hydrologic variability associated with climate scenarios as a function of perturbed climatic variables (e.g. carbon dioxide, temperature, and precipitation). The interannual variation of water resources availability as well as low flow frequency driven by monsoonal time shifts have been investigated to evaluate the likelihood of droughts in a changing climate. The results show that the timing shift of the monsoon window associated with future climate scenarios clearly affect annual water yield change of ? 12 and ? 8% corresponding to 1‐month earlier and 1‐month later monsoon windows, respectively. Also, a more severe low flow condition has been predicted at 0·03 m³/s as opposed to the historic 7Q10 flow of 1·54 m³/s given at extreme climate scenarios. Copyright © 2011 John Wiley & Sons, Ltd.     

Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM) III: Scenario analysis

An ensemble of 10 hydrological models was applied to the same set of land use change scenarios. There was general agreement about the direction of changes in the mean annual discharge and 90% discharge percentile predicted by the ensemble members, although a considerable range in the magnitude of predictions for the scenarios and catchments under consideration was obvious. Differences in the magnitude of the increase were attributed to the different mean annual actual evapotranspiration rates for each land use type. The ensemble of model runs was further analyzed with deterministic and probabilistic ensemble methods. The deterministic ensemble method based on a trimmed mean resulted in a single somewhat more reliable scenario prediction. The probabilistic reliability ensemble averaging (REA) method allowed a quantification of the model structure uncertainty in the scenario predictions. It was concluded that the use of a model ensemble has greatly increased our confidence in the reliability of the model predictions.     

Prediction of the impact of climate change on drought: an evaluation of six UK catchments using two stochastic approaches

Under future climate scenarios, possible changes of drought patterns pose new challenges for water resources management. For quantifying and qualifying drought characteristics in the UK, the drought severity indices of six catchments are investigated and modelled by two stochastic methods: autoregressive integrated moving average (ARIMA) models and the generalized linear model (GLM) approach. From the ARIMA models, autocorrelation structures are first identified for the drought index series, and the unexplained variance of the series is used to establish empirical relationships between drought and climate variables. Based on the ARIMA results, mean sea level pressure and possibly the North Atlantic Oscillation index are found to be significant climate variables for seasonal drought forecasting. Using the GLM approach, occurrences and amounts of rainfall are simulated with conditioning on climate variables. From the GLM‐simulated rainfall for the 1980s and 2080s, the probabilistic characteristics of the drought severity are derived and assessed. Results indicate that the drought pattern in the 2080s is less certain than for the 1961–1990 period, based on the Shannon entropy, but that droughts are expected to be more clustered and intermittent. The 10th and 50th quantiles of drought are likely higher in the 2080s scenarios, but there is no evidence showing the changes in the 90th quantile extreme droughts. Copyright © 2012 John Wiley & Sons, Ltd.     

A statistical methodology for assessing the long‐term effects of antecedent drought conditions on stream runoff: applications to the Piedmont Province,southeastern United States

A method was developed to investigate the long‐term (months‐to‐years) effects (both magnitude and duration) of antecedent rainfall upon subsequent runoff coefficients (RCs) or runoff/rainfall ratios. The method was applied to a four‐state region (Georgia, South Carolina, North Carolina, and Virginia) within the southeastern Piedmont Province of the United States and incorporated a 59‐year data set of 19 United States Geological Survey stream gages and 57 National Climatic Data Center rain gages. The method was designed to facilitate statistical comparisons [Mann–Whitney rank sum tests] between various groups of normalized runoff coefficients (NRCs) representing 6–36 month periods which differed in terms of antecedent rainfall conditions. The results of this study show that under all subsequent rainfall conditions, with the exception of excess rainfall, a 1‐year period of antecedent drought lowered NRCs for at least 1 year following the drought. The principal finding of this study is that a year‐long drought period within the southeastern Piedmont Province lowers NRCs by ～25% during the following year when rainfall returns to normal. In most cases, RCs are significantly lower during the second year following a drought than they would be when anteceded by normal rainfall; however, the effects of drought wane during this period. This is a statistical and regional method that can be modified to other study areas; however, it cannot be used to predict storm‐event rainfall–runoff relationships for any specific basin. Copyright © 2010 John Wiley & Sons, Ltd.     

Meteorological drought analysis using data-driven models for the Lakes District,Turkey

Abstract

Droughts may be classified as meteorological, hydrological or agricultural. When meteorological drought appears in a region, agricultural and hydrological droughts follow. In this study, the standardized precipitation index (SPI) was applied for meteorological drought analysis at nine stations located around the Lakes District, Turkey. Analyses were performed on 3-, 6-, 9- and 12-month-long data sets. The SPI drought classifications were modelled by Adaptive Neural-Based Fuzzy Inference System (ANFIS) and Fuzzy Logic, which has the advantage that, in contrast to most of the time series modelling techniques, it does not require the model structure to be known a priori. Comparison of the observed values and the modelling results shows a better agreement with SPI-12 and ANFIS models than with fuzzy logic models.     

Assessing the impact of the hydraulic properties of a crusted soil on overland flow modelling at the field scale

Soil surface crusts are widely reported to favour Hortonian runoff, but are not explicitly represented in most rainfall‐runoff models. The aim of this paper is to assess the impact of soil surface crusts on infiltration and runoff modelling at two spatial scales, i.e. the local scale and the plot scale. At the local scale, two separate single ring infiltration experiments are undertaken. The first is performed on the undisturbed soil, whereas the second is done after removal of the soil surface crust. The HYDRUS 2D two‐dimensional vertical infiltration model is then used in an inverse modelling approach, first to estimate the soil hydraulic properties of the crust and the subsoil, and then the effective hydraulic properties of the soil represented as a single uniform layer. The results show that the crust hydraulic conductivity is 10 times lower than that of the subsoil, thus illustrating the limiting role the crust has on infiltration. Moving up to the plot scale, a rainfall‐runoff model coupling the Richards equation to a transfer function is used to simulate Hortonian overland flow hydrographs. The previously calculated hydraulic properties are used, and a comparison is undertaken between a single‐layer and a double‐layer representation of the crusted soil. The results of the rainfall‐runoff model show that the soil hydraulic properties calculated at the local scale give acceptable results when used to model runoff at the plot scale directly, without any numerical calibration. Also, at the plot scale, no clear improvement of the results can be seen when using a double‐layer representation of the soil in comparison with a single homogeneous layer. This is due to the hydrological characteristics of Hortonian runoff, which is triggered by a rainfall intensity exceeding the saturated hydraulic conductivity of the soil surface. Consequently, the rainfall‐runoff model is more sensitive to rainfall than to the subsoil's hydrodynamic properties. Therefore, the use of a double‐layer soil model to represent runoff on a crusted soil does not seem necessary, as the increase of precision in the soil discretization is not justified by a better performance of the model. Copyright © 2005 John Wiley & Sons, Ltd.