Diyala River Basin Research Articles

Groundwater Potential Zone Delineation through Analytical Hierarchy Process: Diyala River Basin, Iraq

Groundwater recharge zone identification is vital for managing water resources, particularly in semi-arid and dry climates. Accurate and quantifiable assessment is necessary for the sustainable management of groundwater resources, and it is possible to carry this method out using modern techniques and technical standards. To identify likely groundwater locations in the Diyala River Catchment, Iraq, which serves as an example study basin, the current research examines a new methodology that employs a geographic information system, and an Analytical Hierarchy Process connected with remote sensing data. The technique of ArcGIS was employed to generate spatially distributed thematic layers of rainfall, lithology, slope, drainage density, land use/land cover, relief and soil. The raster data from these layers were then converted and categorized. The weights assigned to thematic strata depended on their significance relative to groundwater occurrence. A pairwise judgement matrix for the Analytical Hierarchy Process was used, with the categorized ranking, to assess the standardized weights of the layers under consideration. The layers for the formation of groundwater zones have then been placed using the overlay-weighted summation approach. Three regions, which are classed as excellent, good and moderate, have been identified on the resulting groundwater potential zones map, representing roughly 29, 69 and 2% of the basin’s total area, respectively. The study’s conclusions indicate that, in such a climate, the adopted strategy would produce favourable results to promote the organizing of opinions and the sustainable use of groundwater resources.

Hydraulic model for flood inundation in Diyala River Basin using HEC-RAS, PMP, and neural network

Abstract The Diyala River Basin in Iraq is vital for water supply to residential, agricultural, and the Tigris River (with approximately 4.5 billion cubic meters annually), but it faces frequent floods and droughts due to reliance on rainfall. This study aims to address these issues by simulating flood inundation using the hydrological engineering centre-river analysis system model and predicting high-intensity rainfall with artificial neural networks. ArcGIS and remote sensing tools aid model development with data from official sources and organizations such as national aeronautics and space administration and food and agriculture organization. The hydraulic model is calibrated using satellite imagery to depict a 2019 flood, and artificial intelligence predicts the precipitation patterns for the next 50 years based on historical data from 1981 to 2021. One of the challenges and difficulties encountered in the study is the scarcity of available data, as well as the absence of scientific research pertaining to the region regarding hydraulic modeling. The study identifies flood risks in March and April every year, notably for the Hemrin Dam, which may exceed permissible water levels (reach a level over 110 m where the Hemrin Crest level is 109.5 m). To mitigate this, an artificial canal is proposed to divert water annually, protecting the dam and downstream areas without disrupting operations. The diverted water could also augment the Tigris River in Kut Governorate during summer. The study demonstrates the value of integrating multiple modeling techniques and data sources for accurate hydraulic predictions. It offers insights for decision-makers in flood management and planning. This study contributes to efficient flood management strategies by adopting a multidisciplinary approach.

Assessment of the impacts of land use/land cover change on water resources in the Diyala River, Iraq

Abstract In this study, the analysis was carried out concerning previous changes in land use/land cover (LULC) for 2 years, 2000 and 2020, and their impact on water resources in the Diyala River Watershed in Iraq was assessed. The Soil and Water Assessment Tool (SWAT) model is a hydrological model used to perform the hydrological modeling process for LULC maps. The data for LULC were collected using the Landsat satellite with a resolution of 30 m, and it was classified using geographical information systems (ArcGIS). Using the confusion matrix, the accuracy of the maps for the years 2000 and 2020 was evaluated, the overall accuracy was more than 90%, and the kappa coefficient (ka) was more than 88%, which indicates the accuracy of the classification and is ideal for use in modeling work. SUFI-2 included with the SWATCUP program was used to perform the calibration and the results were validated for the outflow of the two gauging stations within the study area of Hemren station and Derbendikhan station as a monthly time step for a baseline map LULC 2000, in the period 1996–2020 with 4 years as warm up. Coefficient of determination (R 2), Nash–Sutcliffe efficiency (NSE), and percent bias (Pbias) were used, which were the most common indicators for evaluating the performance of the statistical model. The results indicated that the values of R 2 during the calibration and validation processes were (0.84–0.88) and (0.85–0.87), respectively; the NSE was (0.87–0.85), and the Pbias was (4.2–6.8)% and (5.8 to −4.1)%, respectively. Therefore, the calibration and verification results were good and satisfactory. In addition to the two LULC maps for 2000 and 2020, the parameters of the modified SWAT model were utilized to estimate the effects on the Diyala River Basin. The study found that LULC change affects basins and sub-basins differently. At the basin, hydrological parameters were largely unaffected by LULC changes. However, at the sub-basin level, the water yield and the surface runoff were changed between (−6.45 to 4.67)% and (−2.9 to 9.88)%, respectively.

Resilience Appraisal of Water Resources System under Climate Change Influence Using a Probabilistic-Nonstationary Approach

The planning and management of water resources are being impacted by climate change, and are in need of comprehensive adaptation strategies to respond to future projections. The goal of this study is to support those strategies with a new decision-making paradigm that employs a probabilistic-nonstationary hydroclimatic scenario to examine the long-term system resilience for multiple dam objectives. The modified approach to examine resilience was applied, and uses a bottom-up approach with a modified resilience concept to achieve the long-term operation targets. The approach integrates Global Circulation Models (GCMs) with a statistical weather generator (SWG) to produce a range of future scenarios. Then, the system response is evaluated against those scenarios. The study utilizes a pre-developed SWG to synthesize different trajectories by altering three weather variables: the precipitation amount, temperature mean, and wind-speed magnitude. The proposed has four staged phases: (1) identification of the future climate exposure using different GCMs; (2) future water supply estimation for scenarios using hydrological models; (3) future water demand estimation for scenarios of all system stakeholders; and (4) evaluation of system performance resilience for the dam operational purposes. The Diyala River Basin in Iraq was selected as a case study, to apply the suggested paradigm. The analysis of the GCM outputs revealed that the rainfall mean varies between −37% and +31%; temperature mean varies between +0.4 °C and 5.1 °C; and the mean wind speed varies between −22% and 11%. Based on these ranges, the future climate trajectories were simulated. According to the examination of the system’s response to those weather changes, the precipitation is the most effective parameter, followed by the temperature change, and lastly the wind speed. Furthermore, the findings show that the existing system operating rules are reliable in terms of flood protection but vulnerable in terms of drought management. The analysis of system resilience to manage the drought was found to be 0.74 for the future trajectories, while it was 0.91 for flood protection. This indicates that project managers should prioritize the drought and water scarcity management, due to climate change impact and upstream country development. The study also shows that the suggested resilience paradigm is capable of measuring the negative effects of climate change and able to provide long-term adaptation guidance for water resources management.

Simulation of Rainfall-Runoff in the Diyala River Basin in Iraq using Hydrological Model by HMS with remote sensing, Geo-HMS and ArcGIS

In Iraq, the Diyala River (DR) occasionally experiences both droughts and floods. The DR is supplying the amount of water to Tigris River at the south of Baghdad. Estimation of runoff from precipitation is very important because of its impact on decision-making in water resources management. The conceptual and distributed hydrological model was adopted and by HEC-HMS, Geo-HMS, and GIS software, remote digital elevation models were processed. The sensitivity, calibration, and validation were made through the period 2017-2021. The estimated CN values were from 60 to 100 with distributed related ratios between 0.6% to 52.8%. The differences between the observed and estimated inlet discharge of Hemrin Dam were for (+0.1 to -0.2) % with some more at peak discharge point. The HEC-HMS, using data from NASA and FAO, was acceptable model. The results with an accuracy of 95%, which is indicated by the value of R2 and PBIAS indicators.

Impact of Climate Change on Integrated Management of Water Resources in The lower Basin of Diyala River, Iraq

Climate change could affect the world's water resources system, especially at the level of the basin. Climate change would impact streamflow and corresponding future water resources. The lower basin of the Diyala River is currently experiencing water shortage and contamination issues. This study aims to use Water Evaluation And Planning (WEAP) model to create an integrated modeling system for evaluating the effects of climate change on water supply and demand within the lower Diyala River basin. The WEAP model was calibrated and verified employing monthly streamflow data from the Diyala River outflow station. Following that, the calibrated model was loaded with various future scenarios ranging from 2020-2045. Future scenarios used included the reference scenario, the high population growth rate scenario, and the climate change scenario. The results indicated that the WEAP model accurately predicted the basin's water supply and demand, with RMSE, NSE, and R² values of 0.85, 0.91, and 0.867, respectively, throughout the validation period. Furthermore, Water demand and supply were found to be unmet in all projected future scenarios, showing that sustainable water management in the lower basin of the Diyala River is highly required.

Quantifying Diyala River basin rainfall-runoff models for normal and extreme weather events

Abstract A variety of methods, including both modeling and non-modeling water balance techniques, are used in this study to estimate water availability allocated for different demands. The area under investigation is the shared Diyala River basin between Iraq and Iran, which is vulnerable to climate change impact and upstream control and aims to enhance watershed management. Two rainfall-runoff models were applied, the Tanh curve model and the modified Tanh curve model for runoff simulation at the Derbendkhan and Hemmrin hydrometric stations. Data from two meteorological stations in Iraq (Khanakin and Sulymania) and one in Iran (Sanandaj) for 20 hydrological years (2000–2020) was used. Some goodness of fit indicators were used to evaluate the reliability of the model outcomes, including the correlation coefficient, the root mean squared error, the mean absolute error, the deviation of runoff volume, and the index of agreement. Statistical analysis shows no statistically significant difference between observed and predicted runoff at all stations in winter, spring, and annual time scales when using the Tanh curve model, or for monthly and extreme wet events when using the modified Tanh curve method. The modified Tanh curve model was more accurate than the Tanh model and applied only to Sulymania and Sanandaj stations, as it required a considerable amount of precipitation in at least semi-humid areas.

A Comparative Study of Evapotranspiration Measurement Using SEBAL Model and Atmometer in the Diyala River Basin

Satellite images were taken on the following dates, 1/3/2020, 2/4/2020, 23/3/2020, 24/4/2020, 10/5/2020, 11/6/2020 and 7/13/2020 from the web of the USGS to the area of A.L.- Muqdadiya District, Diyala river basin, Diyala Governorate within (45˚0′7.268̋ and 44˚ 46′ 0.063̋) east and (34˚8′ 47.475̋ and 33˚56′36.621̋) north. The total study area was 736,372 km2, and the area covered with vegetation was 477,606 km2. The SEBAL model was wired to estimate evapotranspiration (E.T.) for the months of the study, both locally and temporally. Remote sensing was used based on satellite Landsat-8 images by sensor OLI as radiation data input. In addition, the meteorological data was used for each date. 28 points were randomly taken within the study area. Atmometer (ETgage) was used to measure daily evapotranspiration, Also the Penman-Monteith equation (FAO56). Was used to estimate E.T. The results showed a good relationship between E.T., estimated by the SEBAL model and measured with an atmometer (R2 = 0.9508). Also, good agreement was showed between SEBAL and FAO 56 (R2 = 0.9913) and atmometer and FAO 56 (R2 = 0.9216). 437 Mm3 of water is required to meet the needs of crops, representing the maximum quantity of water for the study period.

The impact of the Tropical Water Project on the operation of Darbandikhan dam

In addition to global warming and population growth, the Turkish and Iranian water projects have negatively affected the water resources in Iraq. Recently, Iran has implemented its largest water project (The Tropical Water Project – TWP). This project aims to store the flowing water in the Sirwan and Zmkan rivers (i.e., tributaries of the Diyala River) to provide irrigation, domestic, and industrial water for areas inside and outside the Diyala River Basin. The Darbandikhan dam and Halabja water supply project are located on the Diyala River. In this study, the impact of the TWP on the operation of the Darbandikhan dam and Halabja water supply project was investigated. The monthly inflow data of the Darbandikhan dam from September 1991 to December 2017 were used to simulate the operation of the dam using the HEC-ResSim 3.1 package. Two scenarios were adopted for the operation of the Darbandikhan dam. In the first scenario, the Darbandikhan dam operation was simulated without considering the effects of the TWP project.In contrast, in the second scenario, the full operation of the TWP project was considered. The results revealed that about 48.4% of the power generation capacity would be lost, and the water surface elevation in the reservoir would be affected significantly due to the TWP project. The water surface elevation would be at or below 443 m for long periods, which will affect the operation of the Halabja water supply project.

The Impact of the Tropical Water Project on Darbandikhan Dam and Diyala River Basin

Iran has recently started a well-planned project, called Tropical Water Project (TWP), to build more dams, tunnels, and canals on the main tributaries of the Diyala River (Sirwan and Zmkan) to irrigate agricultural areas inside and outside the Diyala River basin. One task in the TWP project is diverting a large volume of the water flowing through the Sirwan and Zmkan rivers through a series of tunnels. The largest one, called Nowsud water conveyance tunnel, transports water from Hirwa dam to Azgala dam to irrigate millions of hectares of new agricultural areas extending from Kermanshah province in the AL Ahwaz province. This research aims to identify the different features and the size of this project as well as the extent of its impact on the Diyala River and Darbandikhan dam. From the results, it was found that the TWP project consists of 14 dams constructed on Sirwan and Zmkan rivers and their tributaries with a total storage capacity of 1.9 Milliard cubic meters and of about 150 km long tunnels to divert more than one Milliard m3 of water to another basin. In addition, it has been found that after the full operation of the TWP project, the catchment area of Darbandikhan dam will lose 77% of its original one.

Hydrologic response of arid and semi-arid river basins in Iraq under a changing climate

Abstract An assessment of the total hydrologic response of arid and semi-arid river basins to various scenarios of climate change by considering evapotranspiration, streamflow, and snowmelt is essential for sustainable management of water resources. The Diyala River Basin in Iraq has been chosen as a typical case study of dozens of river basins in arid and semi-arid regions. Here, the Long Ashton Research Station-Weather Generator (LARS-WG), the Soil and Water Assessment Tool (SWAT), and the SWAT Calibration and Uncertainty Program (CUP) were used to evaluate the total response by considering three Representative Concentration Pathways (RCPs); RCPs 2.6, 4.5, and 8.5 over three periods, 2021–2040, 2041–2061, and 2061–2080. The results indicate that by the year 2080, the basin will experience a temperature increase by 6.6, 10.1, and 16.6% for RCP 2.6, RCP 4.5, and RCP 8.5, respectively. The corresponding reduction in precipitation will be 3.2, 6.4, and 8.7%, resulting in 38.8, 47.9, and 52.8% fall in streamflow for RCPs 2.6, 4.5, and 8.5, respectively. Due to the increase in temperature, an earlier and less contribution of snowmelt is expected in the projected streamflow. Our findings provide a useful reference and a guide to decision makers for developing adaption plans to sustainably manage water resources in the Diyala River Basin and other similar basins in arid and semi-arid regions.

Statistical analysis of extreme weather events in the Diyala River basin, Iraq

AbstractExtreme climate and weather events have direct impacts on human life, the environment, and resources. The Diyala River basin is shared between Iraq and Iran, which makes it vulnerable not only to climate change effects but also to upstream control. Therefore, understanding and predicting extreme events is an essential step to help decision-makers make proactive plans to reduce expected damages. The pattern of extreme events has been identified using climate extreme indices developed by the World Meteorological Organization and Expert Team on Climate Change Detection Indices using ClimPACT2 software. Data were obtained from three meteorological stations in Iraq (Sulaymania, Khanakin, and Baghdad) and one in Iran (Sanandaj) over a period of 20 years (2000–2020). Results for temperature showed seven statistically significant positive trends for only three indices (annual number of days with daily maximum temperature of >35°, difference between daily maximum and daily minimum temperatures, and percentage of days with maximum temperature of >90th percentile, indicating an increase in that temperature). Baghdad station had positive temperature trends for all indices. Trends for precipitation were nearly all nonsignificant and difficult to anticipate compared with those for temperature. Percentile-based indices showed more dry and warm events than wet and cold.

Indices-Based Evaluation of Spatiotemporal Distribution of Drought Within Derbendkhan Dam Watershed

Drought is one of the most significant natural disasters in Iraq. It has a strong impact on the water resources in Iraq. Consequently, it causes massive environmental damage, economic deficiency, and social problems to the country. Therefore, more considerations towards the study and management of drought has become of vital importance in recent decades. In this paper, three drought indices (DIs) were computed for evaluation of the spatiotemporal of drought within Derbendikhan Dam Watershed (DDW) in the Diyala River Basin, Iraq. Based on the monthly weather data for the period (1984 – 2013) downloaded from the Climate Forecast System Reanalysis (CFSR) for eight stations located within DDW. The Reconnaissance Drought Index (RDI), standardized precipitation index (SPI) and Streamflow Drought Index (SDI) at 12-month time scale were computed to assess droughts in the DDW. For each index, the temporal variations of the drought severity and Drought Frequency Patterns (DFPs) for the period (1984 – 2013) were computed and analyzed. In addition, spatial distributions of the drought severity for each index were mapped and investigated. Accordingly, the DFPs were compared to specify the dominant and/or more frequent DFPs. The results show that the performances of different DIs are strongly correlated with the dominant factors of droughts and drought duration. Also, the SPI and SDI are less accurate than the RDI when both precipitation and evaporation are the main factors controlling the drought events. However, the SPI and SDI indices are identical in the same proportions of the dry years which are less than the ratio of dry years to an RDI, but the severity of the drought from the SDI results is higher than the severity of the drought relative to the SPIand RDI. The three indices indicate that the Eastern region is drier than the Western region, which is somewhat wet.

Use Some Spectral Indices to Follow the Flooding of The Diyala River

The examination was directed on the Diyala River Basin, situated inside the territory of Diyala in focal Iraq between longitudes 44º20′ 10.19 ‘-45º 23′ 32.46″ and two latitudes 34º 7′ 56.26″ - 33º 23′ 2.82″ and an area of 5279 km2, the satellite imagery of Landsat 8 OLI_TIRS And derived them spectral indices, using the supervised classification method for the study area and comparing it with the maps prepared from the spectral indices, the study found that the MNDWI guide is the best for monitoring and monitoring the flooding of Diyala River. The statistical values of Kappa showed a good classification for the study area, it ranged between 86-88%.

Characterizing Influence of Hydrologic Data Correlations on Climate Change Decision Variables: Evidence from Diyala River Basin in Iraq

AbstractWater resources decision-making processes involving impacts of climate change require coherent climate datasets, which may exhibit high spatial and temporal variability. These datasets are ...

Development of a Parametric Regional Multivariate Statistical Weather Generator for Risk Assessment Studies in Areas with Limited Data Availability

Risk analysis of water resources systems can use statistical weather generators coupled with hydrologic models to examine scenarios of extreme events caused by climate change. These require multivariate, multi-site models that mimic the spatial, temporal, and cross correlations of observed data. This study developed a statistical weather generator to facilitate bottom-up approaches to assess the impact of climate change on water resources systems for cases of limited data. While existing weather generator models have impressive features, this study suggested a simple weather generator which is straightforward to implement and can employ any distribution function for variables such as precipitation or temperature. It is based on (1) a first-order, two-state Markov chain to simulate precipitation occurrences; (2) the use of Wilks’ technique to produce correlated weather variables at multiple sites with the conservation of spatial, temporal, and cross correlations; (3) the capability to vary the statistical parameters of the weather variables. The model was applied to studies of the Diyala River basin in Iraq, which is a case with limited observed records. Results show that it exhibits high values (e.g., over 0.95) for the Nash–Sutcliffe and Kling–Gupta metric tests, preserves the statistical properties of the observed variables, and conserves the spatial, temporal, and cross correlations among the weather variables in the meteorological stations.

Variable Infiltration-Capacity Model Sensitivity, Parameter Uncertainty, and Data Augmentation for the Diyala River Basin in Iraq

AbstractTo construct a valid model, hydrologists face challenges in determining sensitivity to the forcing data and uncertainty in model parameters. These require basin data and forcing data from d...

Geomorphic processes and active tectonics evaluation in diyala river basin (Iraq-Iran) using the hypsometric curve moment statistical analysis method and its density function

Geomorphic processes and active tectonics evaluation in diyala river basin (Iraq-Iran) using the hypsometric curve moment statistical analysis method and its density function

Decision-Making Challenges of Sustainable Groundwater Strategy under Multi-Event Pressure in Arid Environments: The Diyala River Basin in Iraq

A robust decision-making tool is needed to meet sustainability challenges and to manage water resources that are under development pressure, water scarcity, and climate change impact. To tackle such challenges, optimization modelling can be employed to explore regional sustainable management scenarios of groundwater exploitation. Multi-objective management modelling of various alternatives was developed for the Diyala River Basin in Iraq using Borg multi-objectives evolutionary algorithm (MOEA) and ε-DSEA algorithms. In almost all modelled cases, the upper aquifer storage is predicted to be depleted after 40 years due to large water demands and regional recharge scarcity. Hence, there is a need to develop a strategy to reduce water stresses by 45% to achieve sustainability within the next 25 years. Optimization modelling successfully generated future predictions that can be used by decision makers to manage the predicted groundwater shortages in the future.

Assessment and Mitigation of Streamflow and Sediment Yield under Climate Change Conditions in Diyala River Basin, Iraq

The impact of climate change on the streamflow and sediment yield in the Derbendkhan and Hemrin Watersheds is an important challenge facing the water resources of the Diyala River in Iraq. The Soil and Water Assessment Tool (SWAT) was used to project this impact on streamflow and sediment yield until year 2050 by applying five climate models for scenario A1B involving medium emissions. The models were calibrated and validated based on daily observed streamflow and sediment recorded for the periods from 1984 to 2013 and 1984 to 1985, respectively. The Nash–Sutcliffe efficiency and coefficient of determination values for the calibration (validation) were 0.61 (0.53) and 0.6 (0.62) for Derbendkhan and Hemrin, respectively. In addition, the average of the future predictions for the five climate models indicated that the streamflow (sediment yield) for the Derbendkhan and Hemrin Watersheds would decrease to 49% (43.7%) and 20% (30%), respectively, until 2050, compared with the observed flow of the base period from 1984 to 2013. The spatial analysis showed that 10.4% and 68% of the streamflow comes from Iraqi parts of the Derbendkhan and Hemrin Watersheds, respectively, while 10% and 60% of the sediment comes from the Iraqi parts of the Derbendkhan and Hemrin Watersheds, respectively. Deforestation of the northern part of the Hemrin Watershed is the best method to decrease the amount of sediment entering the Hemrin Reservoir.