MILAD Jajarmizadeh

One of the major issues for semidistributed models is calibration of sensitive parameters. This study compared 3 scenarios for Soil
and Water Assessment Tool (SWAT) model for calibration and uncertainty. Roodan watershed has been selected for simulation of daily flow in
southern part of Iran with an area of 10 570 km2. After preparation of required data and implementation of the SWAT model, sensitivity analysis
has been performed by Latin Hypercube One-factor-At-a-Time method on those parameters which are effective for flow simulation. Then, SWAT
Calibration and Uncertainty Program (SWAT-CUP) has been used for calibration and uncertainty analysis. Three schemes for calibration were
followed for the Roodan watershed modeling in calibration analysis as evolution. These include the following: the global method (scheme 1), this
is a method that takes in all globally adjusted sensitive parameters for the whole watershed; the discretization method (scheme 2), this method
considered the dominant features in calibration such as land use and soil type; the optimum parameters method (scheme 3), this method only
adjusted those sensitive parameters by considering the effectiveness of their features. The results show that scheme 3 has better performance
criteria for calibration and uncertainty analysis. Nash-Sutcliffe (NS) coefficient has been obtained 0.75 for scheme 3. However, schemes 1 and 2
resulted in NS 0.71 and 0.74, respectively, between predicted and observed daily flows. Moreover, percentage bias (P-bias) obtained was 6.7,
5.2, and 1.5 for schemes 1, 2, and 3, respectively. The result also shows that condition of parameters (parameter set) during calibration in SWATCUP
program model has an important role to increase the performance of the model.

Flood is usually an environmental hazard which has been increased in recent years by forcing the pushing factors such as climate change and urbanization. This study presents flood-prone area related to the electric substations for Tenaga Nasional Berhad (TNB) in Peninsular Malaysia. The objective of this research was to identify the related regions that the electric substations are in vulnerable condition by flood risk. For this research, two types of maps are generated, namely flood inundation map (FIM), which indicates the area and capacity of the flood, and flood hazard map (FHM), which provides the area, depth, velocity, and extension of the flood for the TNB’s location of substation. For this issue, different classes of substations are involved in analysis, namely transmission main intake (PMU), main distribution (PPU), main switching station (SSU), and distribution substation (PE). An integration of TNB’s substation maps performed with FIM and FHM due to identify substations which are in flood-prone regions. Generally, result shows that Kelantan is classified as the highest flood-prone region for TNB’s infrastructures especially for PMU which they are affected by flood. Kelantan, Terengganu, and Perlis are involved with the highest flooded, respectively, based on PPU and SSU infrastructure. Finally, for PE substations, Kelantan, Perlis, and Terengganu have the highest contribution for flooded substations for TNB’s structures.

One of the challenging topics in Malaysia is flood occurrence, which have important impacts in human life and socioeconomic subjects. Malaysia, periodically, have faced with huge floods since previous years. Kelantan river basin, which located in the northeast of Peninsular Malaysia, is prone to flood events in Malaysia. Kelantan River has been badly affected with flood during recent monsoon season on December 2014 due to heavy monsoons rainfall and climate change issues. In this study, available rainfall and water-level data are analyzed and presented based on the flood event on December 2014. Generally, the flood area affected includes the districts of Kota Bharu, Kuala Krai, Machang, Pasir Mas, Pasir Puteh, Tanah Merah, Gua Musang, and Tumpat at Kelantan State. In the northeast monsoon season, the Kelantan State suffers from two phase of flood. The first phase began on December 14–17, 2014, and the second phase occurred on December 20–24, 2014. A comparison between accumulated rainfall on December and whole year of 2014 at Gagau station shows that contribution of rainfall on December is roughly 50 % of all of 2014. Overview of water-level results at Kelantan watershed shows that all areas are involved with highest record in 2014 in comparison with previous decades except Golok area. Results of water-level ranges show that most of the parts of Kelantan watershed are involved with over danger values for flood in 2014, which Lebir and Kelantan rivers have high increasing. In conclusion, it is suggested that there is a need to have study on flood mitigation and recognition of critical hydrological phenomena for sustainable strategies in Kelantan watershed. Consequently, this research provides primary information as baseline study for upcoming research for water resource management projects.

Meteorological data are key variables for hydrologists to simulate the rainfall-runoff process using hydrological models. The collection of meteorological variables is sophisticated, especially in arid and semi-arid climates where observed time series are often scarce. Climate Forecast System Reanalysis (CFSR) Data have been used to validate and evaluate hydrological modeling throughout the world. This paper presents a comprehensive application of the Soil and Water Assessment Tool (SWAT) hydrologic simulator, incorporating CFSR daily rainfall-runoff data at the Roodan study site in southern Iran. The developed SWAT model including CFSR data (CFSR model) was calibrated using the Sequential Uncertainty Fitting 2 algorithm (SUFI-2). To validate the model, the calibrated SWAT model (CFSR model) was compared with the observed daily rainfall-runoff data. To have a better assessment, terrestrial meteorological gauge stations were incorporated with the SWAT model (Terrestrial model). Visualization of the simulated flows showed that both CFSR and terrestrial models have satisfactory correlations with the observed data. However, the CFSR model generated better estimates regarding the simulation of low flows (near zero). The results of the uncertainty analysis showed that the CFSR model predicted the validation period more efficiently. This might be related with better prediction of low flows and closer distribution to observed flows. The Nash-Sutcliffe (NS) coefficient provided good- and fair-quality modeling for calibration and validation periods for both models. Overall, it can be concluded that CFSR data might be promising for use in the development of hydrological simulations in arid climates, such as southern Iran, where there are shortages of data and a lack of accessibility to the data

Soil and water are the two major resources in the Earth's hydro biological and geological systems. The hydrology of arid areas has become a topic of interest recently for hydrologists as water shortage at these areas can affect the agriculture, irrigation, and industry as a whole. This has also prompted water resource planners to more thoroughly investigate water resource crisis at arid areas. In this respect, the Soil and Water Assessment Tool (SWAT), a semi-distributed hydrological model, can be a subsidiary tool to be used in the prediction of surface runoff (blue water). This paper presents the application of SWAT on the Roodan watershed, which is located in the southern part of Iran and has 215 mm of annual precipitation. SWAT was engaged to know more about the daily flow and to evaluate the runoff volume. Three continuous scenarios were defined over the 21 years (1988-1992, 1993-2001, 2002-2008) for the land use map as it was found that continuous update of this layer were basically done during these periods. Results of sensitivity analysis showed that parameters related to transmission losses are most sensitive for this watershed. Furthermore, the SWAT had also visualized from the input data that the sub basins which have been designated for agricultural activities from 1988 to 2008 were at the southwest, center and northeast parts of Roodan watershed. Strength of modeling was evaluated by percentage of observations covered by the 95 Percentage prediction uncertainty (P-factor) and relative width of 95 % probability band (R-factor). The P and R factors in this study were recorded at, for calibration and validation periods, 50 % and 0.18 (calibration), and 50 % and 0.17 (validation) respectively. Nash-Sutcliffe and PBIAS obtained for calibration period were 0.75 and 1.5 %, and those for validation period were 0.64 and 21 %. However, results showed an underestimation trend for most peak flows during the modeling of daily stream flow. Nevertheless, the annual runoff volume for calibration and validation periods depicted a promising performance and thus validated the usage of SWAT as a subsidiary hydrological tool for water management projects attributed with stream flow and runoff volume.

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Predicting streamflow in a large arid and semi-arid basin is of great importance in understanding the availability of water for spatial planning and water resource management. In this study, two geographic information system-based (GIS-based) semi-distributed hydrological models were compared for predicting flow. TOPMODEL and SWAT require the use of a GIS to process input data obtained from various sources, such as the digital elevation model (DEM), topographic index (TI), hydrologic response unit (HRU), meteorological stations, and soil- and land-use maps. Daily hydro-meteorological data were collected from 1989 to 2007, and 90-m resolution of DEM was considered. The models were compared, and their performances for the prediction of peak flows and runoff volumes were discussed. TOPMODEL and SWAT obtained good coefficient values for the validation period, i.e., 0.61 and 0.68, respectively. According to relative error percentage (RE %) criteria, TOPMODEL provided a promising value for the validation period (64 %) for peak flows, whereas SWAT provided about 70 %. TOPMODEL provided 5-year overestimation and 1-year underestimation for runoff volume; SWAT provided 2-year underestimation and 4-year overestimation. For this study, both models obtained promising simulation results for surface flow.

Engineering  and  water  resource  management  responses  to  hydrological  variability  depend  on  daily,
monthly and yearly timeframes. Annual runoff volume and flows are significant for long-term decisions on planning
water resources and regulatory programs. The objective of this study was to evaluate the average annual discharge
and runoff volume derived from different time steps run by SWAT (Soil and Water Assessment Tool) as hydrologic
simulator in order to explore the impact of different time step run simulations on yearly runoff yield. Three scenarios
has been performed namely Annual (D), Annual (M) and Annual (Y). Annual (D) and Annual (M) are related with
derived average annual flow from daily and monthly run simulations by SWAT. Annual (Y) is yearly simulation run
via SWAT. The Nash-Sutcliffe (NS) coefficient, Mean Square Error (MSE) and ratio of the Root-MSE (RSR) on
standard deviation of measured data during validation period were 0.73, 6.3 and 0.5 for Annual (D), 0.82, 4 and 0.38
for Annual (M) and 0.81, 4 and 0.38 for Annual (Y), respectively. Also, relative error (%) for validation period
obtained  0.97,  0.35  and  0.33  for  Annual  (D),  Annual  (M)  and  Annual  (Y)  scenarios,  respectively.  The  study
concludes that Annual M and Annual Y scenarios obtained closer results in validation period. In regard to relative
error  for  average  runoff  volume  in  each  year  over  modeling  period,  Annual  (D)  scenario  obtained  highest
contribution with shortest relative errors in comparison with the two other scenarios.