Showing 388 results for Water
A. Ghobadi, M. Cheraghi, S. Sobhan Ardakani, B. Lorestani, H. Merrikhpour,
Volume 26, Issue 1 (5-2022)
Abstract
The qualitative assessment of groundwater resources as the most important sources of drinking and agricultural water is very important. Therefore, the present study was conducted to evaluate the quality of heavy metals in groundwater resources of the Hamadan-Bahar plain in 2018 using water quality indices. In so doing, a total of 120 groundwater samples were collected from 20 stations during the spring and summer seasons and the values of physico-chemical parameters were determined based on the standard methods and also the content of heavy metals was determined using inductively coupled plasma spectroscopy (ICP). The results showed that the mean concentrations of As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn (µg /L) in the samples in the spring season were 5.08, 0.260, 1.05, 2.70, 1.50, 0.490, 1.50, 7.48, and 1.75, respectively, and in the summer season were 20.7, 0.220, 0.950, 7.12, 1.34, 0.490, 1.29, 8.23, and 2.08, respectively and except for As in the summer season, the mean content of other elements was lower than maximum permissible limits established by WHO for drinking water. Meanwhile, the mean values of Cd, HPI, HEI, MI, and PoS indices in the spring season with -7.51, 9.91, 1.42, 1.42, and 328, respectively, indicate the water quality was categorized as low, low, low, low and moderately affected and in the summer season with -5.90, 10.0, 3.04, 3.04, and 673, respectively, were categorized as low, low, low, moderately affected, and high pollution. Due to the extensive use of agricultural inputs, especially chemical and organic fertilizers and chemical pesticides containing heavy metals by farmers in the study area, the possibility of increasing the concentration of heavy metals in the soil and their penetration into groundwater aquifers will not be unexpected in the medium term. Therefore, periodic monitoring in groundwater resources of the study area is recommended.
M. Masoomi, M. Pourgholam-Amiji, M. Parsinejad,
Volume 26, Issue 1 (5-2022)
Abstract
In this study, the Drainmod-S model was used to vary soil salt concentration and the effect of underground drainage on the amount of leaching in a physical model (large lysimeter). A soil extractor was installed at depths of 40, 50, and 70 cm at a distance of 35 cm from the drainage to measure the salinity of the soil solution. In this study, three scenarios were applied including salinity profiles under conventional conditions (mid-season and end-season drainage), soil salinity profiles under different drainage conditions, and prior scenarios with saline irrigation. The second and third scenarios were applied in four drainage stages, respectively. These stages include transplanting and mid-season drainage (days 15 to 20), mid-season drainage (days 35 to 40), mid-season and end-season drainage (days 55 to 60), and end-season drainage (days 75 to 80). The results showed that after simulating the total solute concentration overtime at a depth of 40 cm and comparing it with the measured values, the coefficient of determination (R2) was 0.77 indicating an acceptable Drainmod-S model simulation. This parameter for simulating solute concentration at 50 and 70 cm depth was 0.76 and 0.75, respectively. The mean absolute error parameter (MAE) value was also negligible.
H. Hakimi Khansar, A. Hosseinzadeh Dalir, J. Parsa, J. Shiri,
Volume 26, Issue 2 (9-2022)
Abstract
Accurate prediction of pore water pressure in the body of earth dams during construction with accurate methods is one of the most important components in managing the stability of earth dams. The main objective of this research is to develop hybrid models based on fuzzy neural inference systems and meta-heuristic optimization algorithms. In this regard, the fuzzy neural inference system and optimizing meta-heuristic algorithms including genetic algorithms (GA), particle swarm optimization algorithm (PSO), differential evolution algorithm (DE), ant colony optimization algorithm (ACOR), harmony search algorithm (HS), imperialist competitive algorithm (ICA), firefly algorithm (FA), and grey wolf optimizer algorithm (GWO) were used to improve training system. Three features including fill level, dam construction time, and reservoir level (dewatering) obtained from the dam instrumentation were selected as the inputs of hybrid models. The results showed that the hybrid model of the genetic algorithm in the test period had the best performance compared to other optimization algorithms with values of R2, RMSE, NRMSE, and MAE equal to 0.9540, 0.0866, 0.1232, and 0.0345, respectively. Also, ANFIS-GA, ANFIS-PSO, ANFIS-ICA, and ANFIS-HS hybrid algorithms performed better than ANFIS-GWO, ANFIS-FA, ANFIS-ACORE, and ANFIS-DE in improving ANFIS network training and predicting pore water pressure in the body earthen dams at the time of construction.
N. Salamati, H. Dehghanisanij, L. Behbahani,
Volume 26, Issue 2 (9-2022)
Abstract
Increasing crop production per unit volume of water consumption requires recognizing the most dependent variable in drip irrigation to the volume of water consumption and also identifying the most important variables independent of water productivity in surface and subsurface drip irrigation for optimal use of available water resources. The present research was carried out in Behbahan Agricultural Research Station during four cropping seasons (2013-2017) on a Kabkab date variety. Experimental treatments include the amount of water in the subsurface drip irrigation method based on two levels of 75% and 100% water requirement and in surface drip irrigation based on 100% water demand. Data were analyzed using a randomized complete block design with three replications. The results of the analysis of variance of the mean of different irrigation treatments in quantitative traits showed that the effect of irrigation was significant at the level of 1% in terms of cluster weight index, fruit weight, and fruit flesh to kernel weight ratio. The results of regression analysis of variance showed that in the dependent variable of cluster weight, the consumption water volume explained 19.1% (R2 = 0.191) of the fluctuations of the dependent variable (cluster weight). Among all the studied variables, the volume of water consumption explained the most significant changes in date cluster drying. Fruit moisture with t (2.096) and equivalent beta coefficient (0.046) had a significant positive effect on water productivity at the level of 5%. The results of the Pearson correlation coefficient showed that the effect of yield on changes in water productivity was much greater than the volume of water consumed so the yield caused significant changes in water productivity. While the effect of water consumption on water productivity was not significant.
F. Zarif, A. Asareh, M. Asadiloor, H. Fathian, D. Khodadadi Dehkordi,
Volume 26, Issue 2 (9-2022)
Abstract
An accurate and reliable prediction of groundwater level in a region is very important for sustainable use and management of water resources. In this study, the generalized feedforward (GFF) and radial basis function (RBF) of artificial neural networks (ANNs) have been evaluated for monthly predicting groundwater levels in the Dezful-Andimeshk plain in southwestern Iran. The partial mutual information (PMI) algorithm was used to determine efficient input variables in ANNs. The results of using the PMI algorithm showed that efficient input variables for monthly predicting groundwater level for piezometers affected by water discharge and recharge include only water level in the current month. Also, efficient input variables for predicting the water level for piezometers affected only by water discharge include the water level in the current month, the water level in the previous month, the water level in the previous two months, transverse coordinates of piezometers to UTM, the water level in the previous three months, the water level in the previous four months, the water level in the previous five months and longitudinal coordinates of piezometers to UTM. In addition, efficient input variables of monthly predicting groundwater level for piezometers neither affected by water discharge nor water recharge, respectively, include the water level in the current month, the water level in the previous month, the water level in the previous two months, the water level in the previous three months, the water level in the previous four months, the water level in the previous five months, the water level in the previous six months, transverse coordinates of piezometer to UTM and longitudinal coordinates of piezometer to UTM. The results indicated that the GFF network is more accurate than the RBF network for monthly predicting groundwater level for piezometers including water discharge and recharge and piezometers including only water discharge. Also, the RBF network is more accurate for monthly predicting groundwater levels for piezometers that include neither water discharge nor recharge than the GFF network.
Z. Kolivand, A.r. Pardakhti,
Volume 26, Issue 2 (9-2022)
Abstract
In the past years, by increasing population and water consumption, as well as the high cost of developing surface water resources, the exploitation of groundwater resources has increased significantly. In the current situation, a significant part of the country's water consumption in all sectors of consumption is provided by groundwater sources. On the other hand, the development of industry and the entry of pollutants, including heavy metals, into the groundwater endanger the health of humans. The present research has investigated the non-cancerous risk caused by heavy metals in the groundwater of Urmia plain for both children and adults. This research is based on a descriptive-analytical method based on the available data, in which the concentration of polluting metals obtained from the studies conducted in the fall and winter of 2016 from the number of 12 wells supplying rural drinking water in the Urmia plain has been analyzed. Also, human health risk assessment was measured using the United States Environmental Protection Agency index. The results showed that there are six heavy metals including cadmium, copper, iron, manganese, nickel, and lead in the region's groundwater, among which two of the wells have cadmium and lead values higher than national and international standards. Also, the total non-cancer risk index through ingestion and skin absorption for both children and adults groups was found to be 0.23 and 0.096, respectively, which is less than one, and this indicates that the water quality of the region is suitable for drinking.
A. Motamedi, J. Abedi-Koupai, A.r. Gohari,
Volume 26, Issue 2 (9-2022)
Abstract
Water scarcity and lack of soil fertility are two major problems in the agriculture sector. This study aimed to use Azolla anzali and Lemna minor as a cover for a free surface of the water since not only do they have the potential to reduce evaporation, but they can also produce green fertilizer. Therefore, a completely randomized design experiment with 4 treatments (Azolla anzali, Lemna minor, combination of Azolla anzali+ Lemna minor and control) was performed with three replications. The surface of the reservoirs was covered with the mentioned plants and the changes in water height were measured every other day and the amount of nutrients (nitrogen and phosphorus) of the plant tissue was measured three times at the beginning, middle, and end of the period. Eventually, water loss in tanks containing Lemna, Azolla, and Lemna+ Azolla, was 39, 33.2, and 28.7% less than the control tank. The highest amount of nutrients in plant tissue was observed in Lemna, Azolla+ Lemna, and Azolla treatments, respectively. Although the amount of nutrients in the combined treatment was not higher than that of Lemna more biomass was produced, which means it can provide more fertilizer. Finally, the combined treatment of the two plants is a more suitable option to be used.
T. Tahmasbi, Kh. Abdollahi, M. Pajouhesh,
Volume 26, Issue 2 (9-2022)
Abstract
The runoff curve number method is widely used to predict runoff and exists in many popular software packs for modeling. The curve number is an empirical parameter important but depends largely on the characteristics of soil hydrologic groups. Therefore, efforts to reduce this effect and extract more accurate soil information are necessary. The present study was conducted to integrate fuzzy logic for extraction runoff curve numbers. A new distribution model called CNS2 has been developed. In the first part of this research, the formulation and programming of the CNS2 model were done using the Python programming language environment, then the model was implemented in the Beheshtabad watershed. This model simulates the amount of runoff production in a watershed in the monthly time step with the fuzzy curve number and takes into account the factor of rainy days, the coefficient of management of the RUSLE-3D equation, and the soils theta coefficient. The results indicated that the model with Nash-Sutcliff 0.6 and the R2 coefficient 0.63 in the calibration set and Nash index 0.53 and R2 coefficient 0.56 in the validation set had appropriate efficiency in runoff simulation. The advantage of the model is that distributive and allows for the identification of areas with higher runoff production.
S. Dehghan Farsi, R. Jafari, A.r. Mousavi,
Volume 26, Issue 2 (9-2022)
Abstract
The objective of the present study was to investigate the performance of some of the extracted information for mapping land degradation using remote sensing and field data in Fras province. Maps of vegetation cover, net primary production, land use, surface slope, water erosion, and surface runoff indicators were extracted from MOD13A3, MOD17A3, Landsat TM, SRTM, ICONA model, and SCS model, respectively. The rain use efficiency index was obtained from the net primary production and rainfall map, which was calculated from meteorological stations. The final land degradation map was prepared by integrating all the mentioned indicators using the weighted overlay method. According to the ICONA model, 5.1, 9, 47.21, 27.91, and 10.73 percent of the study area were classified as very low, low, moderate, severe, and very severe water erosion; respectively. Overlaying the ICONA map with other indicators showed that very high and high classes, moderate, and low and very low classes of land degradation covered 1.3, 18.7, 70, 0.9, and 9.1 percent of the study area, respectively. According to the results, integrating remote sensing with ICONA and SCS models increases the ability to identify land degradation.
M. Abdi, H. Sharifan, H. Jafari, Kh. Ghorbani,
Volume 26, Issue 2 (9-2022)
Abstract
The irrigation schedule of crops is the most effective way to increase agricultural water use efficiency. In irrigation planning, determining the irrigation time is more important and difficult than determining the depth of irrigation water. Among all methods of determining the irrigation time of crops, the methods which used plants are more accurate than other methods. In this study, the wheat water stress index has been used which is based on the air vapor pressure deficit and the difference between vegetation and air temperature (Tc-Ta). First of all, the diagram and the relationship between the top and bottom baselines were extracted, then the water stress index of wheat was drawn in the Karaj region. Secondly, to determine the optimal water stress index of wheat, four treatments including I1: 30% of maximum allowable depletion of moisture, I2: 45% of maximum allowable depletion of moisture, I3: 60% of maximum allowable depletion of moisture, I4: 75% of maximum allowable depletion of moisture were performed in four replications. The amount of water stress index of each treatment was calculated during the season separately, and the CWSI of the treatment with the highest water use efficiency was used to determine the irrigation time of wheat. The results showed that the relationship between the upper and lower baseline for wheat in the Karaj region is Tc-Ta = 3.6 0c and
Tc-Ta = -0.27VPD - 2.64, respectively. The treatment of 45% of maximum allowable depletion of moisture had the highest water use efficiency and the optimal water stress index for wheat was obtained at 0.36 in the Karaj region.
P. Fattah, Kh. Hosseini, A.a. Hashemi,
Volume 26, Issue 3 (12-2022)
Abstract
Splash (raindrop) erosion plays an significant role in soil loss, especially in arid and semi-arid regions with poor vegetation. In this paper, by analyzing the pattern of rainfalls that occurred during 26 years in four basins located in Semnan County, their effect on the pattern of eroded sediments from the basin was investigated. Sedimentary layers from the sampling of retarding reservoir sediments in 2017 were related to the corresponding precipitations. Due to the occurrence of the highest amount of rainfall in each quarter of rainfall, rainfall hyetographs were divided into four categories. Cumulative precipitation curves with similar quartiles were drawn in one shape and compared with sediment curves and vice versa taking into account the physical characteristics of the basin. The results showed that the Aliabad basin (with less slope and more elongation) with an effective quarter of type 3 had the highest similarity in precipitation and sediment patterns. Also, the Western Soldereh basin (with the highest slope and the least elongation) with an effective quarter of type 2 had the least similarity in precipitation and sediment patterns. The results indicate the vital role of rainfall patterns on the resulting sediment patterns, which show up to 85% similarity.
M.r. Bahadori, F. Razzaghi, A.r. Sepaskhah,
Volume 26, Issue 3 (12-2022)
Abstract
Inefficient use of limited water resources, along with increasing population and increasing water demand for food production has severely threatened agricultural water resources. One way to overcome this problem is to improve water productivity by introducing new crops that tolerate water stresses such as quinoa. In this study, the effect of water stress at different stages of plant growth (vegetative, flowering, and grain filling) was studied on plant parameters, yield, and water productivity of quinoa (cv. Titicaca). This study was conducted under field conditions and the treatments were performed as a block experiment in a completely randomized design with four replications. Experimental factors were: treatment without water stress or full irrigation (F) and water stress treatment (D) at 50% of the need for full irrigation at different stages of quinoa growth. The application of deficit irrigation during different stages of plant growth decreased stomatal conductance, leaf area index, leaf water potential, seed yield, and water productivity, while deficit irrigation increased the green canopy temperature. According to the results of the present study, the flowering stage of quinoa was very sensitive to water stress leading to produce lower yield compared with the amount of yield obtained when vegetative and or grain filling stages are under water stress conditions.
S. Dehghani, M. Naderi Khorasgani, A. Karimi,
Volume 26, Issue 3 (12-2022)
Abstract
Knowledge of the distribution of heavy metal concentrations in different components of soil particles is significant to assess the risk of heavy metals. The objective of this study was to evaluate some pollution indices and spatial variations in their estimation in different components of soil particle size fractions (<2000 and> 63 μm) in the Baghan watershed in the southeast of Bushehr province with an area of about 929 square kilometers. The location of 120 surficial composite soil samples (0-20 cm) was determined by using the Latin hypercube method. Soil pollution was assessed using geochemical indices of contamination factor (CF) and pollution load index (PLI). The kriging method was used in the Arc GIS software to interpolate the spatial variations of CF and PLI. Based on the results, the CF displayed the particles in the size < 2000 microns compared to all metals in moderate pollution conditions (1≤CF <3) and with the fineness of soil particles (particles with a diameter <63 microns) concerning to Cd metal shows significant contamination status and moderate pollution with other metals, respectively. CFZn, CFCu, and CFFe in particle size <2000 microns and CFPb in finer class were fitted with a spherical model and other metal contamination coefficients with an exponential model. CFCd and CFFe have the highest impact ranges at <2000 and < 63 microns, respectively. The results of this research confirm that corrective operation is needed to monitor cadmium status in the studied area.
G.m. Samadi, F. Mousavi, H. Karami,
Volume 26, Issue 3 (12-2022)
Abstract
The impact of different management options on the region and the existing conditions can be evaluated with minimal cost and time to select the most practical case using various tools including mathematical models. In this study, the SWAT hydrological model was performed from 2009 to 2019 using climatic, hydrological, and hydrometric data in the Malayer catchment, and the final model was validated by SWAT-CUP. To reduce the amount of uncertainty in the input parameters to the MODFLOW model, using the values of surface recharge from the implementation of the SWAT hydrological model, quantitative modeling of Malayer aquifer was performed more reliably in GMS software by using MODFLOW model. After modeling the study area in the 2009-2018 period and calibrating the model in the years from 2018 to 2019, the mean values of absolute error (MAE) were 0.35-0.65 m, and root means square error (RMSE) was 0.62-0.94 m, which seems acceptable considering computational and observational heads equal to 1650 m. Results of water level changes in observation wells located in the Malayer region indicate that the groundwater level in the aquifer has decreased by an average value of 9.7 m in the 10-year study period.
A. Yousefi, M. Maleki-Zadeh, A.r. Nikooie, M.s. Ebrahimi,
Volume 26, Issue 4 (3-2023)
Abstract
This study determines the amount of irrigation water saved as a result of the subsidy policy to adapt from flood to drip irrigation. We developed a positive mathematical programming model (PMP) to evaluate the effect of economic incentives on farmers’ decisions to choose the type of irrigation technology, cropping pattern, and "water use" and "water consumption" in rural Garkan Shomali district, which is part of the Najafabad aquifer. We collected data through farm surveys, desk research, and expert interviews. The results showed that a reduction in the financial costs of converting flood irrigation into drip irrigation can lead to farmers investing in this technology. In the current water allocation scenario, the subsidy policy increases the water consumption of drip-irrigated crops by 28%, of which 19% is non-consumed water before subsidy payment and the rest is related to the reduction of furrow-irrigated lands. Also, under non-volumetric water delivery conditions, the operating costs reduce and the net income of the farms increases because of the increase in efficiency and the development of the area under cultivation, which increases water consumption while the water use is constant. In the volumetric water delivery scenario, with the increase in subsidies, the net income of the farms will increase without developing the area under cultivation and only because of the increased yield. Therefore, subsidy policy increases irrigation efficiency at both the farm and regional levels and is an effective tool for dealing with drought conditions.
F. Zarei, M.r. Nouri Emamzadehei, A.r. Ghasemi Dastgerdi, A. Shahnazari,
Volume 26, Issue 4 (3-2023)
Abstract
The pattern of root distribution in layered soils is one of the significant issues in the calculations of soil water and irrigation management and planning. The objective of this study was to determine the pattern of root distribution of soybean in layered soils and its effect on water uptake. The research was conducted in a completely randomized design with 15 treatments consisting of three different textures of soil (light, heavy, and medium) in four replications. The pattern of root distribution was monitored by the sampling of columns at the end of the growth period of the soybean. It was observed that the presence of the layer with medium texture has led to better plant development and growth after comparing the treatments in terms of plant growth. In general, root length density decreased with increasing soil depth, except in cases where there were different layers of soil, and root length density takes place in the following order: root length density in layers with medium texture≥ heavy texture≥ light texture. The rate of root water uptake rate was highest in the sandy layers, intermediate in clay, and lowest in loamy texture. Also, the rate of root water uptake rate increased significantly with increasing depth regardless of treatments. It can be concluded that the pattern of root distribution and plant growth is significantly affected by soil texture and its stratification.
S. Bigdeli, K. Ebrahimi, A. Hoorfar, A.a. Davudirad,
Volume 26, Issue 4 (3-2023)
Abstract
In this study, the accuracy of the Adaptive Network-Based Fuzzy Inference System (ANFIS) in integrating with the Gray Wolf Algorithm (ANFIS-GWO) in predicting groundwater level was evaluated for the first time using unpublished observational data from 1998 to 2018 in the Zarandieh aquifer, central Iran. Three observational wells were randomly selected for analysis. Assessment of evaluation criteria demonstrated that among the proposed scenarios using the hybrid model, the D scenario was selected as the optimal scenario with input data including the previous month's groundwater level, precipitation, temperature, and groundwater extraction. In the D scenario, parameters including MAPE, RMSE, and NASH were 0.29 m, 0.47 m, and 0.99, respectively for the first observational well. Also, C scenario with input data including the previous month's groundwater level, precipitation, and groundwater extraction for the second observational well, for the same parameters mentioned above equal to 0.20 m, 0.26 m, and 0.99. As well for the third observational well, the A scenario with input data including the previous month's groundwater level for the same parameters equal to 0.29 m, 0.41 m, and 0.99 as the optimal scenarios were selected using the ANFIS-GWO model. Based on the results, the Gray wolf algorithm in training the ANFIS model was able to reduce the average forecast error by equal to 0.03 (RMSE) and 0.02 (MAPE) meter and increased the average NASH value equal to 0.01 and increased the accuracy of predictions.
M. Farzamnia, M. Miran Zadeh,
Volume 26, Issue 4 (3-2023)
Abstract
The present study was carried out in the Mahyar region of Esfahan Province to determine optimum drip tape spacing for the wheat crops on a silty clay loam soil respecting grain yield as well as yield components, water use efficiency, and variations in the salinity within the soil profile. The experiment was performed for three years from 2017 to 2019 with a randomized complete block design with three replicates and four treatments. The treatments consisted of three tape spacings (A) at 45, (B) at 60, (C) at 75 cm, and the Control (D) was irrigated with the basin method. The same volume of irrigated water was applied to the drip treatments, A, B, and C in every irrigation interval, whereas for treatment D, the local farmers’ practice was followed. Based on the results from compound variance analysis, the treatment effect on both grain yield and biological yield, and on water use efficiency and harvest index was significant at 1% and 5% level of confidence, respectively. The mean water use efficiency in treatments A, B, C, and D was measured as 0.79, 0.79, 0.73, and 0.78 kg m-3; thus, treatments A, B, and D outperformed treatment C. A comparison between the salinity of the soil profile at the beginning and the end of the growing season revealed that the basin irrigation method was more effective on salt leaching than the drip tape system. The results of this study indicated that concerning water use efficiency and crop yield, drip tapes spaced at 45 or 60 cm outperformed those which were 75 cm apart. On the other hand, the work required for irrigation system installation as well as the amount of drip tape residues left on the field at the end of the growing season is larger for tapes spaced at 45 cm compared to those which are 60 cm apart. This will have a significant impact on farmers’ budgets and environmental issues. Therefore, it is recommended to lay the tapes 60 cm apart for the irrigation of wheat crops on silty clay loam soils.
B. Shahinejad, A. Parsaei, H. Yonesi, Z. Shamsi, A. Arshia,
Volume 26, Issue 4 (3-2023)
Abstract
In the present study, the flow rate in flues containing lateral semi-cylinders (SMBF) was simulated and estimated under free and submerged conditions using back vector machine models (SVM), spin multivariate adaptive regression (MARS), and multilayer artificial neural network (MLPNN) model. In free flow mode, the dimensionless parameters extracted from the dimensional analysis include the ratio of upstream flow to throat width and contraction ratio (throat width to channel width), and in the submerged state, in addition to these two parameters, the depth-to-throat width, and bottom-depth parameters upstream depth were used as input and the two-dimensional form of flow rate was used as the output of the models. The results showed that in free flow mode in the validation stage, the MARS model with statistical indices of R2 = 0.985, RMSE = 0.008, MAPE = 0.87%, and the SVM model with statistical indices of R2 = 0.971, RMSE = 0.0012, MAPE =1.376%, and MLPNN model with statistical indices of R2 = 0.973, RMSE = 0.011, MAPE = 1.304% have modeled and predicted the flow rate. In the submerged state, the statistical indices of the developed MARS model were R2 = 0.978, RMSE = 0.018, MAPE = 3.6%, and the statistical indices of the SVM model were R2 = 0.988, RMSE = 0.014, 2%. MAPE = 4, and the statistical indicators of the MLPNN model were R2 = 0.966, RMSE = 0.022, and MAPE = 5.7%. In the development of SVM and MLPNN models, radial kernel and hyperbolic tangent functions were used, respectively.
T. Mohammadi, V. Sheikh, A. Zare,
Volume 26, Issue 4 (3-2023)
Abstract
Trend analysis of stream flow provides practical information for better management of water resources on the eve of climate change. Therefore, the present study investigated river flow variations during three decades as well as projections of future discharge in the Gorganrood watershed. The Man-Kendall method has been used to detect the trend and methods of Pettitt, SNHT, and Buishand to identify points of a sudden change in discharge time series in 8 stations of Aq Qala, Galikesh, Gonbad, Haji Ghoshan, Nodeh, Ramyan, Sadgorgan, and Tamar. The Mann-Kendall trend test showed the existence of a significant negative trend (flow reduction) on a daily and annual scale in all stations. Monthly, the strongest negative trend in Aq Qala, Galikesh, Gonbad, Haji Ghoshan, and Ramyan stations was related to July, but in Nodeh and Tamar stations, it was related to August and February, respectively. A decreasing trend was observed in all stations on a seasonal scale, but this trend was not significant in some seasons. The results of the analysis of change points in discharge showed that the change points in the data used in this study are more of a decreasing and in some cases incremental type and some stations, no change points have been identified at all. Therefore, the number of decreasing changes in the studied hydrometric stations is significantly higher than the incremental changes and is more visible from 1993 to 1997 and 2005-2007 in three and four stations, respectively. Also, the most incremental changes among the stations are related to the Aq Qala station in 2017 with a flow rate of 234 cubic meters per second. Investigation of the flow of the basin in the past decades showed significant monotonic and abrupt changes which are mostly toward decreasing the basin’s discharge. The downward trend in discharge values at different time scales for all hydrometric stations of the Gorganrood watershed, which will be more severe in the future due to global climate change, and increasing the region's water needs for various future use due to population growth and the expansion of industries can also be considered as a serious warning for policymakers, planners, and local managers to prevent a possible water crisis in the region in the future with proper planning.
