Studying and Assessing Surface Water Use of Shuwaija Marsh within Wasit Governorate-Iraq

T his study aims to study and evaluate the surface water use of Al-Shuwaija marsh by estimating the maximum value of water flow and the volume of water revenues through the hydrological analysis of the characteristics of these marsh basins in addition to the physical analysis of the characteristics of the selected design storm. The hydrological model was created for the watersheds of the Al-Shuwaija marsh. Sixty simulations were conducted to model the Shuwaija marsh for different return periods and rainstorms, where the model was calibrated and then validated to predict the flow and volume of water using the (WMS) program. The SCS method was used to calculate the value of the total curve number (CN) based on the land use and soil type of Al-Shuwaija marsh basins, where its value was 80.84. It has been shown via modelling that a discharge may be achieved into 8298 m 3 /sec at a return period of 100 years and obtain a discharge of up to 1775 m 3 /sec at a return period of 2 years. Based on the expected amount of precipitation that would fill the selected reservoir, three scenarios were assumed each scenario representing the area of the reservoir and the volume of incoming water.


INTRODUCTION
The major risk of the Iraqi marshes drought is still unless decisive action is taken, such as conducting a comprehensive study and planning for water resources by estimating the amount of water for various stages of the hydrological cycle and their return periods and studying the future of water resources (Adamo et al., 2018).The lack of water sources during droughts, in addition to climate change, has a clear impact on the marshes.Therefore, it is necessary to evaluate hydraulic and hydrological behavior by estimating the amount of water revenue through rainfall (Ali et al., 2023) (Mandali, Qazania, Tursaq, Mirzabad, Galal Badra, al-Chabbab, al-Teeb, and Dwaireeg) using regression models developed for the western and southern United States.The optimal investment in a region's natural water resources is one strategy to provide large quantities of water that may help mitigate the harmful effects of climate change (García-Ruiz et al., 2011).In watershed research, it is crucial to conduct a thorough evaluation of the parts of any hydrological system (Manhi and Al-Kubaisi, 2021).(Abbas and Abdulameer, 2020) used the Landsat series of images to identify flood waters in Al-Shuwija marsh from 1972 to 2019, as well as to track the geographical extent and spread of flooding.The effects of climate change, as well as the fact that these wetlands have no outlets during times of low flow.So, it is important to assess the hydraulic behaviour and quality of the marsh water and determine the optimal position of the output drains (Al-rikabi and Abed, 2021).(Hasan et al., 2021) calculated the highest and lowest water levels in the Al-Shuwija marsh basin and provided quantitative information on the size of the flooded areas to use in future planning and research using Landsat pictures .(Abed and Abduljabbar, 2022) analyzed the potential impact of upgrading the flooding of Al-Shuwija marshes using a geographic information system, and more specifically the QGIS tool.Moreover, a digital elevation model was used to examine the wetlands, with 28 m spatial resolution, and applying the Watershed Modeling System (WMS), to estimate the surface runoff over the watershed was performed.The software ARC-GIS and the WMS, were frequently used to simulate terrain models and to extract watersheds runoff (Kamal et al., 2018).An assessment of water budget and flow estimates was conducted using the results produced from meteorological models with control specifications with local meteorologic data that were used to conduct the simulation of the basin model's precipitation-runoff response (Kazezyılmaz-Alhan et al., 2021).The current study aims to develop a numerical model to simulate surface runoff in Al-Shuwaija Marshrivers using WMS software to forecast the amount of water that the marsh will receive from the basins of the local rivers Galal Badra and Tarsaq.

Watershed Modeling System (WMS)
As it is well known to the specialists, the Watershed Modeling System (WMS) software provides a wide range of analyses of the hydrologic environment

The Study Area
Al-Shuwaija Marsh is roughly six kilometers from Kut City's northern region, has coordinates (3611873.86-3631813.39) N and (590379.11-585830.23

The Input Data
In this research, the Digital Altitude Model (DEM), Land Cover/Usage Map, Soil Map, and Weather were used, in addition to calibrating and verifying the WMS mode using the curve number and the observed Galal Badra discharge as references.

The Digital Elevation Model (DEM) and the Triangulated Irregular Network (TIN)
The WMS model requires topography as a necessary input because it enables the analysis of land surface features and the process of determining flow directions and watersheds (Fathy et al., 2019).One technique developed to represent relief is the Digital Elevation Model (DEM) (Jenson, 1991).The procedure of creating a model of the Earth's surface using previously gathered data is known as DEM building (Hapep and Maythm, 2020).Furthermore, its effects extend to the velocity and direction of flow across the planet's surface.Thirty-meter resolution digital elevation models are available for download at https://earthexplorer.usgs.gov/.Global Land Survey (GLS) http://www.usgs.gov/landsat;this land cover is one of the best that is accessible, and it is offered at a resolution of 30 meters, as shown in Fig. 5.Each land parcel's Curve Number, which characterizes a catchment's reaction to a storm event, has been approximated using the LU layer and soil layer present within (Shukur, 2017).

Slope
The

Watershed Analysis
The watershed analysis included using a DEM to draw flow lines and routes and determine watersheds.The WMS software has defined watersheds using the DEM-based technique, allowing for the identification of many sub-basins within each watershed.Each subbasin's flow rate is determined.

Drainage Area
The drainage area is the land area from which precipitation drains into creeks, streams, rivers, and lakes.It is a land feature that may be determined manually or automatically by drawing a line along the greatest elevation between two regions on a map.Calculating the amount of precipitation and establishing the watershed's curve number both need the drainage area, which is an essential component.Consequently, the drainage area is an input for the hydrological model used to predict peak flow and runoff volume.The drainage region encompasses 11937 km².Fig. 7 shows the drainage system in the research area.3 shows the CN number that was derived for each of the identified subwatersheds.The curve number (CN) value for the sub-watersheds in the research region varies from 85 to 78.The weighted curve number for the whole watershed.Using WMS's (Compute Travel Time) function from the calculators' menu, the study's subwatershed journey times were computed.After that, the appropriate input parameter for the chosen hydrologic model was given the calculated journey time.Result in the window for Tc computation in WMS.Table 4 shows the Time of Concentration (TC) that was acquired for each of the defined sub-watersheds.Time of concentration (Tc) values for the sub-watersheds in the research region vary from 10.817 hours to 33.623 hours.As the longest route in the watershed has a Tc of 47.80 hours, that's the total Tc for the whole watershed.

Watershed Delineation
Based on the direction of flow accumulation, WMS automatically determines four sites as outflow points for a watershed.Table 5 shows the watershed's characteristics.The Watershed's discharge point is where the SCS hydrograph was collected.This result was produced using the HEC-1 model for a storm of varying intensity duration and return periods.The hydrograph is shown in Table 7.The lake would be filled to a capacity of 342319565 m 3 with a surface area if it received 95 mm of precipitation (300 km²).Scenario No. 1, lake filling within boundaries, is shown in Fig. 11.With 130 mm of precipitation, the lake would reach its volume of (6153674140 m³) and its surface area of (550 km²).Lake filling within boundaries is shown in Fig. 12.

Third Scenario (Depth of Precipitation of 75 mm)
With 75 mm of precipitation, the lake would reach its volume of (184253485 m³) and its surface area of (185 km²).Lake filling within boundaries is shown in Fig. 13.Table 8 shows all the information used in the scenarios to calculate the peak discharge and volume of water and surface area for the Shuwaija reservoir.

CONCLUSIONS
The main results of this study contributed to rain forecasts in estimating water quantities, the surface water quality during dry and inundation seasons, and the impact of the sewage treatment plant were evaluated through the following conclusions; a) Loamy soil makes up the majority (78%) of the soil type in Al-Shuwaija marsh.
As the SCS method was used to estimate the peak discharge for each sub-basin, we now know that the peak discharge at the outflow of watershed Al-Shuwaija is 1775, 2945, 4214, 5540, 6906, and 82984 m 3 /s for the 2, 5, 10, 25, 50, and 100-year return periods, respectively.b) This research creates a footprint for Al-Shuwaija watersheds in the form of flowduration-frequency (FDF) curves, which allow us to calculate the peak discharge for a given storm duration and return period.c) To implement effective measures for the economic and social development of the Al-Shuwaija watersheds, the findings of this research are very significant for the local authorities.The research confirms that the amount and rate of water flow recorded may be captured and stored in Shuwaija Reservoir.Moreover, the model may be used to make storage predictions in light of precipitation data.d) The model is calibrated by changing the CN of the watershed Al-Shuwaija since it contributes to the flow at the monitoring station in Badra city; the results of calibration were successful and logical, so the model is validated to predict flow discharge and volume at the watershed outlet across a range of time scales and return periods.e) The water levels decreased significantly during July to reach 40 cm, in addition to the decrease in the flooded area of the marsh to reach half its area in March as a result of several factors, the most important is the evaporation of large quantities of water as a result of high temperatures, shallow depths of water and the extended areas of the marsh.

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Predicting floods requires an understanding of the likely quantities of precipitation to come (Al-Mudaffar et al., 2016).Observed precipitation may be converted into stream flow with the use of hydrological models (AL-Heetimi et al., 2015).(AL-Thamiry and Hassani, 2015) found that the restoration of the entire marshes is not achievable under the current conditions due to the limited discharge of water from the feeders of the Iraqi marshes and the decline in nutrition from the Iranian side.(Hilo and Saeed, 2019) investigated the quality and amount of water in the streams that flow into Al-Shuwaija marsh, as well as improved water management.Different hydrological processes in watersheds are significantly impacted by climate change (Luo et al., 2013).Water resources management relies heavily on accurate estimates of surface runoff from rainfall in water basins (Farhan and Abed, 2021).(Rahi et al., 2019) investigated the runoff of eight catchment regions (Erturk et al., 2006).The software was created by the Waterways Experiment Station which belongs to the U.S. Army Corps of Engineers by the Environmental Modeling Research Laboratory at Brigham Young University (ECG) (Yannopoulos et al., 2005).While there is only one storm event per Watershed Modeling System (WMS), there are multiple modeling options.. T Using a DEMbased approach, watersheds have been defined by the WMS software, making it possible to identify numerous sub-basins inside each watershed (Srinivas et al., 2018).The flow rate of each subbasin is established.. Following the WMS form's setup and completion of all required data entry, The program starts examining the basins' spatial data (Deliman et al., 2002).
) E, as shown in Fig. 1.It is a naturally occurring, rectangular depression that the Tigris River flows alongside (Al-Shamaa and Ali, 2011).

Figure 1 .
Figure 1.Site of the Study area (ESRI World Street) Fig.s 2 and 3 display the study area's TIN and DEM maps.

Figure 4 .
Figure 4. Soil groups map of the study watershed slope is the rate of height change per unit mile along the route of the main channel (Begin et al., 1981).It is an essential component of the runoff's momentum, which has a bearing on the size of floods (Najafi, 2003).The DEM is used to determine the slope.The variance in slope % throughout the research region is shown in Fig. 6.

Figure 5 .Figure 6 .
Figure 5. Land use in the study area 3.1.2Watershed LengthA watershed's length is measured from its outlets along the main channel to its division point, and it increases as the watershed's surface area increases.It is essential to estimate the concentration time.The longest trail in the watershed of the study area is (140 km for Galal Badra and 235 km for the Tursaq River) as shown in Fig.8.

Figure 7 .
Figure 7.The drainage system at Figure 8.The watershed with the the watershed main channels

Table 5 .
The watersheds characteristics 3.1.6Generated Thiessen polygons Using (WMS 11.1) software, the weighted ratio for each effective rainfall station is determined by applying the Thiessen polygons.Thiessen polygons for the three rainfall stations in the watershed of the study area are shown in Fig.9.The contribution ratio of each rainfall station to the overall 11937 km² area, as well as the contribution area for each rainfall station.

Figure 9 .
Figure 9. Generated Thiessen polygons for all rainfall station

Figure 10 .
Figure 10.Peak discharges compared between simulations and estimates VOLUME SCENARIOS FOR THE AL-SHUWEJA MARSHTo study the projections of water quantities for the Al-Shuwaija marsh under the influence of climate change, we will have three proposals the scenarios are listed below: 4.1 First Scenario (Depth of Precipitation of 95 mm)

Figure 11 .
Figure 11.Scenario No.1, Filling of the bounded lake

Figure 12 .
Figure 12.Scenario No.2, filling of the bounded lake

Table 1 .
Characteristics of Soils Assigned to Soil Groups I dry, but above the wilting point Less than 13 Less than 36 II average (normal).III wet (saturated soil).More than 28 More than 53

Table 2 .
shows the characteristics of rainfall stations in the study area.

Table 3 .
The CN curve number for all watersheds

Table 4 .
Time of concentration value for all sub-watersheds

Table 6 .
The observed and the simulated results at the calibration drainage for the Galal Badra watershed

Table 7 .
Peak flow (m 3 /sec ) for the study area.

Table 8 .
Details of scenarios computation