Integrating water use systems and soil and water conservation measures into a hydrological model of an Iranian Wadi system

Water resources are precious in arid and semi-arid areas such as the Wadis of Iran. To sustainably manage these limited water resources, the residents of the Iranian Wadis have been traditionally using several water use systems(WUSs) which affect natural hydrological processes. In this study, WUSs and soil and water conservation measures(SWCMs) were integrated in a hydrological model of the Halilrood Basin in Iran. The Soil and Water Assessment Tool(SWAT) model was used to simulate the hydrological processes between 1993 and 2009 at daily time scale. To assess the importance of WUSs and SWCMs, we compared a model setup without WUSs and SWCMs(Default model) with a model setup with WUSs and SWCMs(WUS-SWCM model). When compared to the observed daily stream flow, the number of acceptable calibration runs as defined by the performance thresholds(Nash-Sutcliffe efficiency(NSE)≥0.68, –25%≤percent bias(PBIAS)≤25% and ratio of standard deviation(RSR)≤0.56) is 177 for the Default model and 1945 for the WUS-SWCM model. Also, the average Kling–Gupta efficiency(KGE) of acceptable calibration runs for the WUS-SWCM model is higher in both calibration and validation periods. When WUSs and SWCMs are implemented, surface runoff(between 30% and 99%) and water yield(between 0 and 18%) decreased in all sub-basins. Moreover, SWCMs lead to a higher contribution of groundwater flow to the channel and compensate for the extracted water by WUSs from the shallow aquifer. In summary, implementing WUSs and SWCMs in the SWAT model enhances model plausibility significantly.

Simulation of water quantity exchange between groundwater and the Platte River water, central Nebraska

The authors demonstrate the importance of the simulation of the water quantity exchange between river water and groundwater to a better understanding of the hydrologic relations between a river and nearby aquifer where groundwater is pumped extensively but only seasonally. And MODFLOW is used to design the stream aquifer model in which the pumpage of more than 1000 wells was simulated. The river gaining and river losing processes were analyzed. Simulation results suggest that continuation of over extraction of groundwater will gradually increase the depletion volume in the river year after year and more depletion will occur in later years. The exchange manner between groundwater and the Platte River differs from place to place. The Platte River loses water to the adjacent aquifer in the west part of the study area, and gains water from the adjacent aquifer in the east part of the study area.

Assessing the Influence of Global Climate and Anthropogenic Activities on the Water Balance of an Andean Lake

Tropical regions along the Andean Cordillera face an uncertain future as mountain lakes and snow peaks exhibit receding trends associated with factors such as climatic precursors and local anthropogenic activities. Tota, the largest mountain lake in the Colombian Andes, exemplifies the role played by these factors on the lake's hydrologic evolution. A monthly water balance in Tota Lake was performed using available hydrological information from 1958 to 2007 to address interannual and multiannual level fluctuations associated with human activities and climatic precursors. The balance shows that net water uses fluctuated around 2 m3/s during this period with a pattern that, although constrained during years of severe decline in lake levels, is able to explain most of the multiannual decaying trend of 1.5 cm/year in the last 50 years. The lake’s naturalized levels were used to determine the influence of climate precursors on the lake evolution. Using Multichannel Singular Spectrum Analysis (M-SSA), significant five-year ENSO and 20-year PDO related quasi-oscillations were detected, explaining 54% of the variance associated with mean annual naturalized level fluctuations. ENSO is markedly in-phase with lake levels, with critical declines associated with low precipitation and high evaporation rates during El Ni?o years, whereas the PDO signal exhibits a phase opposition with lake levels, with low naturalized levels during a positive PDO phase and high levels during a negative PDO phase (an important result to consider given the current cooling trend of the PDO signal).

Comparison of smoothness-constrained and geostatistically based cross-borehole electrical resistivity tomography for characterization of solute tracer plumes

Experiments using electrical resistivity tomography(ERT) have shown promising results in reducing the uncertainty of solute plume characteristics related to estimates based on the analysis of local point measurements only.To explore the similarities and differences between two cross-borehole ERT inversion approaches for characterizing salt tracer plumes,namely the classical smoothness-constrained inversion and a geostatistically based approach,we performed two-dimensional synthetic experiments.Simplifying assumptions about the solute transport model and the electrical forward and inverse model allowed us to study the sensitivity of the ERT inversion approaches towards a variety of basic conditions,including the number of boreholes,measurement schemes,contrast between the plume and background electrical conductivity,use of a priori knowledge,and point conditioning.The results show that geostatistically based and smoothness-constrained inversions of electrical resistance data yield plume characteristics of similar quality,which can be further improved when point measurements are incorporated and advantageous measurement schemes are chosen.As expected,an increased number of boreholes included in the ERT measurement layout can highly improve the quality of inferred plume characteristics,while in this case the benefits of point conditioning and advantageous measurement schemes diminish.Both ERT inversion approaches are similarly sensitive to the noise level of the data and the contrast between the solute plume and background electrical conductivity,and robust with regard to biased input parameters,such as mean concentration,variance,and correlation length of the plume.Although sophisticated inversion schemes have recently become available,in which flow and transport as well as electrical forward models are coupled,these schemes effectively rely on a relatively simple geometrical parameterization of the hydrogeological model.Therefore,we believe that standard uncoupled ERT inverse approaches,like the ones discussed and assessed in this paper,will continue to be important to the imaging and characterization of solute plumes in many real-world applications.

Uniqueness, scale, and resolution issues in groundwater model parameter identification

This paper first visits uniqueness, scale, and resolution issues in groundwater flow forward modeling problems. It then makes the point that non-unique solutions to groundwater flow inverse problems arise from a lack of information necessary to make the problems well defined. Subsequently, it presents the necessary conditions for a well-defined inverse problem. They are full specifications of （1） flux boundaries and sources/sinks, and （2） heads everywhere in the domain at at least three times （one of which is t = 0）, with head change everywhere at those times being nonzero for transient flow. Numerical experiments are presented to corroborate the fact that, once the necessary conditions are met, the inverse problem has a unique solution. We also demonstrate that measurement noise, instability, and sensitivity are issues related to solution techniques rather than the inverse problems themselves. In addition, we show that a mathematically well-defined inverse problem, based on an equivalent homogeneous or a layered conceptual model, may yield physically incorrect and scenario-dependent parameter values. These issues are attributed to inconsistency between the scale of the head observed and that implied by these models. Such issues can be reduced only if a sufficiently large number of observation wells are used in the equivalent homogeneous domain or each layer. With a large number of wells, we then show that increase in parameterization can lead to a higher-resolution depiction of heterogeneity if an appropriate inverse methodology is used. Furthermore, we illustrate that, using the same number of wells, a highly parameterized model in conjunction with hydraulic tomography can yield better characterization of the aquifer and minimize the scale and scenario-dependent problems. Lastly, benefits of the highly parameterized model and hydraulic tomography are tested according to their ability to improve predictions of aquifer responses induced by independent stresses not used in the inverse modeling efforts.

Integrated Interpretation of Geophysical and Soil Geochemical Anomalies in Gold Exploration: Case of Kouremale, Southern Mali-West Africa

Detecting the anomalies’ sources location in the vast territory such as Kouremale area is a grand challenge for geophysicists because there is a need to assess gold deposit. Therefore, this paper aims to recommend a methodological approach on applied magnetic survey and soil geochemistry to identify the location of anomalies’ sources. To that aim the study is divided into phases. In the first phase, the maps for integrated interpretation have been produced by Geosoft Oasis and ArcGIS 10.2.1. The corrected and processed magnetic data with eliminated diurnal variation have been used. Phase two consist of integrate geochemical soil map. The results of phase one identified four magnetic anomalies zones (MAZ) with their coordinates. Thus, the obtained radiometric map, showed that there is a high intensity of K and Th compared to U, which indicates a significant weathering process and there are many saprolithes in study area. The findings of phase two revealed that there is a high concentration of gold content (1500 ppm) with an average concentration of 92 ppm. The integrated interpretation map coming from the combined different maps, referring to the geological information verified on the field, led to conclude that, the target B is the best gold anomaly. The delimitation of the space of the target B from the geophysical and geochemical information confirmed the existence of limited, restricted and potential anomaly.

Bacterial Influence on Textile Wastewater Decolorization

The study aims to isolate and optimize bacterial strains having the ability to degrade and decolorize azo dyes produced in the final effluent of textile dying industries. In this regard, ten bacterial strains were isolated from wastewater treatment plants, and most of them were subjected to the colored effluents resulting from dilapidated houses. The ability of these bacterial isolations to use a wide range of azo dyes to determine the sole carbon source was determined. According to these screening testes, two bacterial isolations were selected as the most potent decolorizer for azo dyes, and they were identified as Comamanas acidovorns-TN1 and Burkholdera cepace-TN5. The optimization process started with the addition of 1 g/l yeast extract, where the decolorization ability of the two strains increased sharply and according to this experiment, the two azo dyes, Acid orange 7 and Direct blue 75, were selected to complete the study. The effect of different conditional and chemical factors on the decolorization process of Acid orange 7 and Direct blue 75 by Comamanas acidovorns-TN1 and Burkholdera cepace-TN5 was studied. Factors that contributed to the difference were different pH, temperature, incubation period, inoculum size, carbon source, nitrogen source and the respective concentrations of yeast extract. This study recommends the application of the two most potent bacterial strains in the decolorization of the azo dyes, along with acid orange 7 and direct blue 75, specifically in the industrial effluents under all nutritional and environmental conditions.

Photooxidation of Furfural with Phthalocyanine-sensitized TiO_2 Particle Under Xenon Lamp

Copper phthalocyanine was selected as the photosensitizer to sensitize TiO2 in this experiment with furfural as the target pollutant. The composite catalysts（TiO2/CuPC） obtained showed a great activity under a xenon lamp. By experiments, the optimal preparation conditions of the composite catalysts were set as follows ： the CuPC loading mass fraction was 1.5%, the mass fraction of acetylacetone was 0. 3% , and the stirring time was 10 h. UV-Vis diffuse reflectance spectra, XRD, and BET were used to characterize the properties of the composite catalysts, which showed that after loading CuPC on TiO2, the composite catalyst retained the same crystal structure as pure TiO2 and the wavelength range of its absorption spectrum was broadened to 600-700 nm while its surface area was smaller than that of the pure TiO2. Under the optimal conditions, 20 mg/L furfural solution was degraded by nearly 90% and TOC by about 70%. When the catalyst was reused 6 times, the activity of the catalyst was still retained by about 75%.

Effects of heterogeneity distribution on hillslope stability during rainfalls

The objective of this study was to investigate the spatial relationship between the most likely distribution of saturated hydraulic conductivity(Ks) and the observed pressure head(P) distribution within a hillslope. The cross-correlation analysis method was used to investigate the effects of the variance of ln Ks, spatial structure anisotropy of ln Ks, and vertical infiltration flux(q) on P at some selected locations within the hillslope. The cross-correlation analysis shows that, in the unsaturated region with a uniform flux boundary, the dominant correlation between P and Ksis negative and mainly occurs around the observation location of P. A relatively high P value is located in a relatively low Kszone, while a relatively low P value is located in a relatively high Kszone. Generally speaking, P is positively correlated with q/Ksat the same location in the unsaturated region. In the saturated region, the spatial distribution of Kscan significantly affect the position and shape of the phreatic surface. We therefore conclude that heterogeneity can cause some parts of the hillslope to be sensitive to external hydraulic stimuli(e.g., rainfall and reservoir level change), and other parts of the hillslope to be insensitive. This is crucial to explaining why slopes with similar geometries would show different responses to the same hydraulic stimuli, which is significant to hillslope stability analysis.

Comparison of two different methods for determining flow direction in catchment hydrological modeling

Digital elevation models （DEMs） are widely used to define the flow direction in distributed hydrological models for simulation of streamflow. In recent decades, numerous methods for flow direction determination have been applied successfully to mountainous regions. Nevertheless, some problems still exist when those methods are used for flat or gently sloped areas The present study reviews the conventional methods of determining flow direction for such landscapes and analyzes the problems of these methods. Two different methods of determining flow direction are discussed and were applied to the Xitiaoxi Catchment, located in the Taihu Basin in southern China, which has both mountainous and flat terrain. Both the agree method and the shortest path method use drainage networks derived from a remote sensing image to determine the correct location of the stream. The results indicate that the agree method provides a better fit with the DEM for the hilly region than the shortest path method. For the flat region where the flow has been diverted and rerouted by land managers, both methods require observation of the drainage network to determine the flow direction. In order to clarify the applicability of the two methods, both are employed in catchment hydrological models conceptually based on the Xinanjiang model and implemented with PCRaster. The simulation results show that both methods can be successfully applied in hydrological modeling. There are no evident differences in the modeled discharge when using the two methods at different spatial scales.

Allometric relationships between primary size measures and sapwood area for six common tree species in snow-dependent ecosystems in the Southwest United States

High-elevation,snow-dependent,semiarid ecosystems across southwestern United States are expected to be vulnerable to climate change,including drought and fi re,with implications for various aspects of the water cycle.To that end,much less is known about the dynamics of transpiration,an important component of the water cycle across this region.At the individual-tree scale,transpiration is estimated by scaling mean sap fl ux density by the hydroactive sapwood area(SA).SA also remains a key factor in eff ectively scaling individual tree water-use to stand level.SA across large spatial scales is normally established by relating SA of a few trees to primary size measures,e.g.,diameter at breast height(DBH),tree height(H),or canopy diameter(CD).Considering the importance of SA in scaling transpiration,the primary objective of this study was therefore to establish six species-specifi c(aspen,maple,white fi r,ponderosa pine,Douglas fi r,Englemann spruce)allometric relationships between SA and three primary size measures(DBH,CD,or H)across two high-elevation,snow-dependent,semiarid ecosystems in New Mexico and Arizona.Based on multiple statistical criteria(coeffi cient of determination,index of agreement,Nash–Sutcliff e effi-ciency)and ease of measurement in the forest,we identifi ed DBH as the primary independent variable for estimating SA across all sites.Based on group regression analysis,we found allometric relationships to be signifi cantly(p<0.05)diff erent for the same species(ponderosa pine,Douglas-fi r)across diff erent sites.Overall,our allometric relationships provide a valuable database for estimating transpiration at diff erent spatial scales from sap fl ow data in some of our most vulnerable ecosystems.

Modeling the Effect of Irrigation Practices in Flash Floods: A Case Study for the US Southwest

Conventional streamflow forecasting does not generally take into account the effects of irrigation practice on the magnitude of floods and flash floods. In this paper, we report the results of a study in which we modeled the impacts of an irrigated area in the US Southwest on streamflow. A calibrated version of the Variable Infiltration Capacity model (VIC), coupled with a routing algorithm, was used to investigate two strategies for irrigating alfalfa in the Beaver Creek watershed (Arizona, USA), for the period January to March of 2010, at a resolution of 1.8 km and hourly time step. By incorporating the effects of irrigation in artificially maintaining soil moisture, model performance is improved without requiring changes in the resolution or quality of input data. Peak flows in the watershed were found to increase by 10 to 500 times, depending on the irrigation scenario, as a function of the strategy and the intensity of rainfall. The study suggests that both flood control and irrigation efficiency could be enhanced by applying improved irrigation techniques.

Development of Upstream Data-Input Models to Estimate Downstream Peak Flow in Two Mediterranean River Basins of Chile

Accurate flood prediction is an important tool for risk management and hydraulic works design on a watershed scale. The objective of this study was to calibrate and validate 24 linear and non-linear regression models, using only upstream data to estimate real-time downstream flooding. Four critical downstream estimation points in the Mataquito and Maule river basins located in central Chile were selected to estimate peak flows using data from one, two, or three upstream stations. More than one thousand paper-based storm hydrographs were manually analyzed for rainfall events that occurred between 1999 and 2006, in order to determine the best models for predicting downstream peak flow. The Peak Flow Index (IQP) (defined as the quotient between upstream and downstream data) and the Transit Times (TT) between upstream and downstream points were also obtained and analyzed for each river basin. The Coefficients of Determination (R2), the Standard Error of the Estimate (SEE), and the Bland-Altman test (ACBA) were used to calibrate and validate the best selected model at each basin. Despite the high variability observed in peak flow data, the developed models were able to accurately estimate downstream peak flows using only upstream flow data.

On Redefining the Onset of Baseflow Recession on Storm Hydrographs

Two methods that define the point of baseflow recession onset were compared using storm hydrograph data for 27 storm events that occurred between 1982-1995 in the Upeo watershed located in the Andes mountain range in central Chile (Figure 1). Three well-known baseflow recession equations were used to determine whether the method we are proposing here, that defines baseflow recession onset as the third inflection point on the logarithmic graph of the falling limb of the storm hydrograph, more accurately models observed data than the most widely used method that defines baseflow onset as the second inflection point on the same graph. Five time intervals were used to modify the recession coefficient in search of a more accurate fit. Results from the coefficient of determination, standard error, Mann-Whitney U test, and Bland-Altman test suggest that redefining baseflow recession onset via the proposed approach more accurately models baseflow recession behavior.

Assessing the Performance of Two Hydrologic Models for Forecasting Daily Streamflows in the Cazones River Basin (Mexico)

Floods have caused significant human and economic losses in the Cazones River Basin, located on the Gulf of Mexico. Despite this knowledge, steps towards the design and implementation of an early warning system for the Cazones are still a pending task. In this study we contributed by establishing a hydrological scheme for forecasting mean daily discharges in the Cazones Basin. For these purposes, we calibrated, validated and compared the HyMod model (HM) which is physics-based, and an autoregressive-based model coupled with the Discrete Kalman Filter (ARX-DKF). The ability of both models to accurately predict discharges proved satisfactory results during the validation period with RMSEHYMOD = 2.77 [mm/day];and RMSEARX-DKF = [2.38 mm/day]. Further analysis based on a Streamflow Assimilation Ratio (SAR) revealed that both models underestimate the discharges in a similar proportion. This evaluation also showed that, under the most common conditions, the simpler stochastic model (ARX-DKF) performs better;however, under extreme hydrological conditions the deterministic HM model reveals a better performance. These results are discussed under the context of future applications and additional requirements needed to implement an early warning hydrologic system for the Cazones Basin.

运用水力层析法对含水层裂隙带成像

含水层裂隙带的识别,是准确模拟计算地下水流和污染扩散的前提。本研究通过数值实验,运用近年来发展起来的水力地质层析方法,对含水层裂隙带成像。文章设定一个17m×17m的二维垂直饱和裂隙含水层,含水层有2口斜井。在斜井与裂隙带的交叉点分别进行抽水试验,由感应器收集水位响应数据,运用VSAFT2对裂隙带进行识别。数值实验证明,水力层析法结合地下水流的逆算方法——连续线性算法(SSLE),可以比较准确地识别非均质含水层的参数分布;非稳定流条件下的识别结果好于稳定流的结果;信息齐全条件下的结果好于资料缺乏时的结果。

HUBEX强化观测期雷达测雨在水文过程模拟中的应用(英)

On the basis of Digital Elevation Model data, the raster flow vectors, watershed delineation, and spatial topological relationship are generated by the Martz and Garbrecht method for the upper area of Huangnizhuang station in the Shihe Catchment with 805 km2 of area, an intensified observation field for the HUBEX/GAME Project. Then, the Xin’anjiang Model is applied for runoff production in each grid element where rain data measured by radar at Fuyang station is utilized as the input of the hydrological model. The elements are connected by flow vectors to the outlet of the drainage catchment where runoff is routed by the Muskingum method from each grid element to the outlet according to the length between each grid and the outlet. The Nash-Sutcliffe model efficiency coefficient is 92.41% from 31 May to 3 August 1998, and 85.64%, 86.62%, 92.57%, and 83.91%, respectively for the 1st, 2nd, 3rd, and 4th flood events during the whole computational period. As compared with the case where rain-gauge data are used in simulating the hourly hydrograph at Huangnizhuang station in the Shihe Catchment, the index of model efficiency improvement is positive, ranging from 27.56% to 69.39%. This justifies the claim that radar-measured data are superior to rain-gauge data as inputs to hydrological modeling. As a result, the grid-based hydrological model provides a good platform for runoff computation when radar-measured rain data with highly spatiotemporal resolution are taken as the input of the hydrological model.

Laplace-Transform Finite Element Solution of Nonlocal and Localized Stochastic Moment Equations of Transport

Morales-Casique et al.(Adv.Water Res.,29(2006),pp.1238-1255)developed exact first and second nonlocal moment equations for advective-dispersive transport in finite,randomly heterogeneous geologic media.The velocity and concentration in these equations are generally nonstationary due to trends in heterogeneity,conditioning on site data and the influence of forcing terms.Morales-Casique et al.(Adv.Water Res.,29(2006),pp.1399-1418)solved the Laplace transformed versions of these equations recursively to second order in the standard deviationσY of(natural)log hydraulic conductivity,and iteratively to higher-order,by finite elements followed by numerical inversion of the Laplace transform.They did the same for a space-localized version of the mean transport equation.Here we recount briefly their theory and algorithms;compare the numerical performance of the Laplace-transform finite element scheme with that of a high-accuracy ULTIMATE-QUICKEST algorithm coupled with an alternating split operator approach;and review some computational results due to Morales-Casique et al.(Adv.Water Res.,29(2006),pp.1399-1418)to shed light on the accuracy and computational efficiency of their recursive and iterative solutions in comparison to conditional Monte Carlo simulations in two spatial dimensions.

A Piecewise Modeling Approach for Climate Sensitivity Studies:Tests with a Shallow-Water Model

In model-based climate sensitivity studies, model errors may grow during continuous long-term inte- grations in both the ＂reference＂ and ＂perturbed＂ states and hence the climate sensitivity （defined as the difference between the two states）. To reduce the errors, we propose a piecewise modeling approach that splits the continuous long-term simulation into subintervals of sequential short-term simulations, and updates the modeled states through re-initialization at the end of each subinterval. In the re-initialization processes, this approach updates the reference state with analysis data and updates the perturbed states with the sum of analysis data and the difference between the perturbed and the reference states, thereby improving the credibility of the modeled climate sensitivity. We conducted a series of experiments with a shallow-water model to evaluate the advantages of the piecewise approach over the conventional continuous modeling approach. We then investigated the impacts of analysis data error and subinterval length used in the piecewise approach on the simulations of the reference and perturbed states as well as the resulting climate sensitivity. The experiments show that the piecewise approach reduces the errors produced by the conventional continuous modeling approach, more effectively when the analysis data error becomes smaller and the subinterval length is shorter. In addition, we employed a nudging assimilation technique to solve possible spin-up problems caused by re-initializations by using analysis data that contain inconsistent errors between mass and velocity. The nudging technique can effectively diminish the spin-up problem, resulting in a higher modeling skill.