IRAN-WATER RESOURCES RESEARCH
Year:2016 | Volume:12 | Issue:1|Papers Count:17

Policy making in Integrated Water Resources Management relies on understanding the concept of vulnerability. Therefore, it will be essential to identify the socio-economic state of the system under study as well as its hydrological state. In this paper, a water accounting framework is adopted to make a basis for integrated water resources management to embrace socio-economic aspects as well as the hydrological feature. The water accounting framework will be capable of integrating different data from economic, hydrological, and social domains. It is also suitable to address the effects of different policies. The aim of the present paper is to analyze vulnerability of the water resource system in the Rafsanjan study area. Adopting an analytical framework for assessing the system vulnerability to water scarcity, the paper then presented a derivation of vulnerability indicators based on the data organized in terms of different water accounts for 2001 and 2006. Analyzing the trends of indicators, the paper suggested policy options which could be applied in those periods to reduce the system vulnerability. The policy options are then simulated in a system dynamics model (using the VENSIM PLE software) built in association of the water resource and economic sub-systems of the study area. The results showed that the water resource system of the study area is highly vulnerable to water scarcity. To alleviate the system vulnerability, the policy options are suggested to shift partly from agricultural activities to industrial and mining activities.

Nowadays, a lot of models are offered by researchers to estimate surface evapotranspiration (ET) based on meteorological and remote sensing data. Quality of prepared/processed input data has a pivot role on final accuracy of calculated actual ET. In this regard, inputs of a model should be evaluated cautiously before starting the study regarding the effect of each data on the model outputs as well as the required processing cost and time. In this study, actual ET in Shahrkord plain was calculated using Landsat8 satellite images and the proposed daily energy balance model. Results showed a good consistency with lysimeter, pan evaporation and potential ET. The sensitivity of calculated ET to key parameters of the model was then studied with different density of canopy and ET on Julian days of 147, 195 and 291 in 32 control points. Finally, these results were compared with the sensitivity analysis results of SEBAL model studied previously by Khavarian Nahzak (1004). The results showed that the data of group A including air temperature, land surface temperature (LST), income short radiation, and sunny hours, group B including relative humidity and albedo, and group C including the sensitivity of leaf area index and wind have high, medium to high, and low to medium sensitivity, respectively. Thus, it is recommended recording the most sensitive data with more accuracy. Finally, the sensitivity analysis results of proposed daily model showed a considerable similarity with SEBAL model, except for LST.

The aim of this study is to link drought monitoring systems to management actions in surface water systems. For this purpose drought early warning system is applied. In order to assess the proposed approach, water resources system of Zarine-rud River and Reservoir was used. Management actions includes utilizing coefficients that decrease the release from the reservoir. In each drought warning level, a reduction coefficient is computed by a Multi-Objective Genetic Algorithm. Utilizing the model during the entire historic period, the number of alerts is decreased on levels two to four by 18, 80, and 10%, respectively. Also, by applying reduction coefficients during index drought period, deficits above 80% decreased to less than 50% over six months. The effect of model in condition of supplying the environment water right of Urmia Lake is also evaluated. Applying reduction coefficients during index drought, the deficits above 50% is decreased to less than 30% over 14 months. This research showed that model had an appropriate function in warning declaration in long term periods. The assessments indicated the achieved results from the model are accurate and acceptable and therefore the application of this method is recommended.

Sistan plain is located in Hirmand River delta which is the only source of water for the plain. The plain has therefore the highest level of dependency on transboundary water resources in national scale. In spite of many studies – mostly focusing on supply side management practices - the observations are implying unsustainability and vulnerability of the area to the Hirmand river discharge variations. Analyzing the Sistan plain vulnerability to water scarcity, the paper adopts the vulnerability framework developed by Fussel. To apply the framework, the system attributes of concern in terms of socio-economic and biophysical features need to be determined. Thus, the value added and total population were considered to represent the socio-economic features of the vulnerable system and the water reservoir associated to Lake Hamoun was considered as the biophysical feature. Then, in order to reduce the system vulnerability to water scarcity, this study suggested applying the theory of transition resilience which is in line with the real local conditions towards self-organized changes in the area. The economic local condition is transforming from purely agricultural towards activities with less dependency on water which is, somehow, an adaptation to the water scarcity conditions. In this way, the paper seeked for economic changes to bring the local welfare in the water scarcity conditions back to that associated to the water abundant conditions. Therefore, five resilience levels have been defined as the reference levels for the system associated to the input annual water discharge to the area between 3000 to 5000 MCM. A system dymamic model was applied to determine the values associated to the system attributes of concern according to the five levels of the system resilience until 2050. Then, necessary changes were introduced to the system to satisfy the reference resilience levels under the condition that the river annual input discharge would decrease to 700 MCM (90 percent of Iran’s water right from Hirmand River). The values of local water productivity and also the total volume of allocated water to economic uses necessary to satisfy the reference resilience levels were represented in terms of two curves. For instance, to bring the system into an equilibrium condition the model outputs suggested that increasing water productivity to 56000 Rial per Cubic meter (according to the base price of 2011) with 240 MCM of maximum water volume supplly will lead to residence of 1 million inhabitants with 16 million IRR annual income per capita (according to the base price of 2011) till 2010. However, the water reservoir in Lake Hamoun would never get back to its initial condition.

The probable maximum precipitation (PMP) and probable maximum flood (PMF) are among the important measures in designing hydraulic structures. One of the most suitable statistical techniques for estimating PMP is Hershfield method. In this study the maximum 24 hours precipitation was evaluated using 12-53 years of data from 6 rain gauge stations and 1 synoptic station located in Qareh-su basin. For this goal two statistical methods of Hershfield (in two different approaches of standard and revised) were used. For the first approach, frequency factor and the PMP24 were found to vary in the range of 16.98 to 18 and 335.08 to 524.93 mm, respectively. The corresponding values for the second approach was 2.06 to 4.01 and 88.35 to 153.41 mm, respectively. Also the amount of PMP24 with 50 and 100 year return periods using Gumbel distribution were respectively calculated as 579.2 and 613.59 mm in the first approach and 263.69 and 281.7 mm in the second approach. As a criterion independent to the climate conditions, the ratio of PMP24 to the maximum of 24 hours precipitation was used for compare PMP in stations. The results indicated that the second approach was more stable for the Qareh-su basin. The Precipitation Gradient was then investigated for drawing the isohyets maps which presented an insignificant. Therefore the Inverse Distance Weighted method was used to draw the iso-PMP maps and to determine the Depth-Area-Duration curves. Using these curves, conversion of point PMP24 to areal PMP24 over Qareh-su basin is Possible.

This study highlights the need to improve the estimation of the water resources performance criteria such as reliability, resilience and vulnerability (RRV) regarding common approaches. The study also proposes a new technique to obviate disadvantages of common (classic) approaches. RRV criteria are very useful for evaluating performance of water resources system which are used in many researches in the last three decades. This study explains that common approaches of quantifying these estimators have unreliable performance in thresholds of desired values of parameters under investigation such as water supply. This weak point in previous approaches has been shown by an evident example, demonstrating that this problem could change exact values of reliability, resilience and vulnerability in evaluating the water resource system performance. This would also lead to incredible inaccuracy in evaluating the sustainability index of a water system. This study developed an approach to improve PRV performance criteria for water resource systems performance evaluation. The new relations are based on previous formulas with improvements in their structures using the concept of membership functions in fuzzy theory. The Zayandehrud basin has been used as a case study to compare and assess the new and previous approaches. Comparison of the results of the new proposed approach with those of the common approaches to estimate performance criteria as well as their summaries by sustainability index showed that the new approach is very effective and practical meanwhile eliminating disadvantages of common approach.

Management of groundwater resources, especially in arid and semi-arid areas, has great importance. Natural and anthropogenic phenomena in recent decades have caused critical conditions and fall in groundwater table. In such situations artificial recharge of groundwater is amongst the most important management strategies. Purpose of this study is the use of AHP and statistical methods (fuzzy-statistical ranking and parameters optimization of artificial recharge model based on nonlinear regression and sensitivity analysis) to determine suitable areas of artificial groundwater recharge in Kashan aquifer. In this study, SMAGR artificial recharge model was used for site selection artificial recharge in Kashan aquifer based on seven parameters of groundwater contamination (GC), soil infiltration rate (IR), capability of hydraulic conductivity (HC), soil pollution (SP), land use (LU), topographic slope (TS), and water table (WT). Adding layer of aquifer pollution risk was also used for site selection of suitable areas based on considerations of groundwater environmental conditions. The information layers were prepared in GIS environment and the fuzzy-statistical rating was combined based on geometric mean with equal weights. In addition, removal sensitivity analysis was used to determine the effective weight of parameters and to optimize the model. Based on the results obtained from statistical method and optimized model about 15% and 0.1% of the western and southern parts of aquifer are suitable to very suitable for artificial recharge. Also the sensitivity of the model showed a decreasing trend associated to different parameters of removed groundwater contamination, soil infiltration rate, hydraulic conductivity, soil pollution, land use, topographic slope and water table with effective weights of 2.96, 2.83, 2.41, 2.33, 2.21, 2.07 and 1.89, respectively.

This study investigates the effects of climate changes on the runoff of the Firoozabad River located in Fars Province, Iran. In order to downscale the output of the atmospheric circulation model, LARS-WG software was used in the base station and software SDSM is used in the upper station. In order to select atmospheric circulation models that fit the studied area, the initial weighting was used as the screening element. To examine the effects of climate changes on the runoff, ANN trained with ICA algorithm was used. The results of investigating the climate changes indicate the increase of temperature between 0.7 to 1.8oC for the minimum temperature and the increase of 0.7 to 1.7oC for the maximum temperature. Although the increase of precipitation was very low, the results indicate the increase of 2 to 12% of the rainfall. The results also indicate the decrease of runoff in April, May, June, and October and the increase of runoff in the other months. Considering the uncertainty, the highest runoff uncertainty is observed in January and April.

SA method is known as one of the most effective metaheuristic numerical methods for solving complex optimization problems. In this method after determining the appropriate combination of SA parameters and the final implementation of the algorithm for the problem considered, the results should be evaluated using an appropriate approach. Hence in this paper an initiative method named the asymptote is presented and it is shown how the SA algorithm will converge to the asymptote of the global optimum and also presents a value for global optimum. The method is applied to solve 5 problems which have analytical solutions and it led to a reasonable estimate of the global optimum where the minimum, maximum and average error was 0.6, 10, and 5 percent, respectively. Also 5 models of ICSSDOM, OPTIFUR, SOP-SA, BISEDOM and ARM-SA is verified by asymptote method for optimization of hydraulic performance of water distribution channels, furrow irrigation, optimal operation of reservoir, border irrigation and sediment distribution of dam reservoir, respectively. As a result, asymptote method can be used for validation of SA algorithm results when there is not valid criteria to assess them.

Modeling of wetlands and lakes pollution is necessary for development and land allocation, management, water quality monitoring, prevention of pollution and conservation of biodiversity. In this study, physico-chemical parameters of EC, TDS, DO, pH, NO3-, PO43-, SD, TP, TN, and Chl.a, pollution and biological indices of TSI & BMWP and organic matters (OM) were used for assessment of pollution and anthropogenic impact on water quality in Choghakhor wetland in Chaharmahal Bakhtiari province, Iran. Sampling stations were selected on systematic non-random base for the sampling and measurement. Sampling was performed of wetland surface and in depth of 50 centimeter from 12 stations 1 kilometer in distance in six stages and in 45 day intervals. Then the spatial model of surface and depth average of qualitative parameters, soil organic matters, and TSI and BMWP indices was prepared using interpolation functions based on cross validation technique (lowest value of RMSE, highest value of R2 and lowest close to zero values of spatial data MBE and MAE) of deterministic and geostatistical methods in GIS environment. The results of spatial-temporal modeling for the period of 2003 to 2005 showed that values of TSI, BMWP, and OM indices with moderate values of 61, 31 and 40% are in eutrophy and bad status and the values are higher (more pollution) in south and west half of wetland due to land use activities. Also TSI, PO43- and DOsat parameters have meaningful temporal correlations and BMWP, OM, TDS and Depth parameters has significant spatial correlations. Also results of spatial-temporal modeling of TSI (2005-2006) determined the highest pollution in spring and autumn seasons (eutrophic moderate of 67-70) which is hypertrophy of 70-74 in south half due to anthropogenic and land use impact. The value is lowest in summer season showing the lower pollution with eutrophic moderate of 59.

Optimization of monitoring network is the best possible process for decision-making among existing networks. Considering economical objectives and for reducing the cost of monitoring, optimization approach is based on decreasing monitoring stations in this study. Using an algorithm based on entropy and nitrate pollution index, optimizing the monitoring network was conducted with 287 wells in the period of 2002 to 2011. First, the average of each station rank was calculated based on statistical years. Then, some models were proposed for the network entropy in terms of station numbers and time. After fitting the best network entropy model, the results showed that 111 wells are sufficient as groundwater quality monitoring stations for Mashhad aquifer. In order to approve the proposed network, 111 random networks were selected in each year, and by comparing the entropy of those networks to the proposed network, the performance of selected network was confirmed. Also, the selected network performance was confirmed for the future of Mashhad aquifer.

According to the nonlinear relationship among the components of aquifers these systems are called as complex systems. Due to natural and artificial changes the estimating the degree of complexity of these systems is very important for groundwater quality and quantity assessments. In this study multi-scale entropy (MSE) theory was applied to analyze long-term variation piezometers (1985-2014) in order to ascertain impacts of Saveh dam on the complexity of the Saveh aquifer plain located downstream of the dam. In this approach, unlike the sample entropy that calculates only the amount of entropy for a single scale factor, the MSE was used to assess the possible changes in the complexity of the aquifer in multi scale factors. The results showed that the complexity of the aquifer after the construction of Saveh dam decreased precipitously from the beginning of the aquifer plain to its middle line. An average of 31 percent increase can be seen in the entropy difference between the samples (complexity) in two periods (before and after the dam construction). The complexity properties alterations of the aquifer caused the destruction of natural systems aquifer and decrease the complexity of it. The comparison between proposed approach and Mann-Kendall method indicated the efficiency of MSE in evaluating the complexity of aquifer systems and detection of abnormal events in the groundwater table level time series. This study provided a reference for conservation of the aquifer natural environment and the assessment of impacts induced by big hydraulic structures on the groundwater system.

The aim of this study is a comparison among two multi-site stochastic weather generators for simulation of winter rainfall occurrence across Iran using data of a selected network consisting of 190 rain gauge stations with a historical data of 11 years. The applied approaches included Hidden Markov Model (HMM) as a parametric approach and K-nearest neighbor (KNN) as non-parametric approach. Six stations namely, Bandar Anzali, Sari, Gharakhil Ghaemshahr, Gorgan, Shiraz and Zahedan were chosen respectively as the representative of different climates including very humid, humid, semi humid, Mediterranean, semi dry and dry climates. In comparison of first and second order momentums, results indicated that HMM performed well in almost every station. Data dispersion was examined using box plot and confidence interval analysis. The results revealed better performance for HMM. Regarding probabilities spaces, HMM showed a better performance in simulation of extreme events and higher percentiles of empirical distribution but KNN approach provided better estimations for middle percentiles values. LEPS Score index was used for comparison of cumulative distribution of observed and simulated series which showed more agreement in case of HMM. The spatial correlation was evaluated using Log-odds ratio index, which indicated that KNN model did better. Both approaches performed well in estimation of duration of wet and dry spells though a tendency to overestimate was observed at HMM and a tendency to underestimate viewed at KNN in simulating of wet spells. In general, HMM has more skill in simulation of daily rainfall series which might be attributed to its complex mathematical structure, however relatively good results of KNN approach showed that it can be recommended for less complicated applications.

Climate could be known as a set of atmospheric conditions of a dynamic and chaotic system. However, a fundamental problem in estimating the chaotic time series dimension is dealing with the fact that a temporal signal of any natural phenomenon is always contaminated by noise. The objectives of this study are: a) investigating the effect of noise reduction in daily maximum temperature time series on the reconstructed phase space, time delay and embedding dimension; b) quantifying chaos for both time series before and after noise reduction, by using methods such as maximal Lyapunov exponent and correlation dimension; and c) comparing the prediction accuracy in both time series. For this study, we used daily maximum temperature time series of Kerman station for 25 years (1984-2008 AD). The results showed that the embedding dimension and delay time in time series after the noise was reduced (respectively, 5 and 76 days) from those of before (respectively 7 and 82 days). In both time series, the positive maximal Lyapunov exponent (respectively, 0.011 and 0.019) and low correlation dimension (respectively, 2.78 and 2.85) resemble the chaotic system. However, noise reduction can have some effects on quantifying chaos and the accuracy of prediction by reducing the random component, so, for the analysis of nonlinear dynamics of time series, noise reduction is essential, but this reduction should not destroy the determinism component of the system