The lack of sufficient precipitation data has been a common problem for water resource planning in many arid and semi-arid regions with sparse and limited weather monitoring networks. Satellite-based precipitation products are often used in these regions to improve data availability. This research presents the first validation study in Syria for Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) estimates using in-situ precipitation data. The validation was performed using accuracy and categorical statistics in the semi-arid Barada Basin, Syria, between 2000 and 2020. Multiple temporal scales (daily, pentad, monthly, seasonally, and annual) were utilized to investigate the accuracy of CHIRPS estimates. The CHIRPS results indicated advantages and disadvantages. The main promising result was achieved at the seasonal scale. Implementing CHIRPS for seasonal drought was proven to be suitable for the Barada Basin. Low bias (PB_winter = 2.1%, PB_wet season = 12.7%), high correlation (r_{wet season} = 0.79), and small error (ME = 4.25 mm/winter) support the implementation of CHIRPS in winter and wet seasons for seasonal drought monitoring. However, it was observed that CHIRPS exhibited poor performance (inland pentads) in reproducing precipitation amounts at finer temporal scales (pentad and daily). Underestimation of precipitation event amounts was evident in all accuracy statistics results, and the magnitude of error was higher with more intense events. CHIRPS results better corresponded in wet months than dry months. Additionally, the results showed that CHIRPS had poor detection skill in drylands; on average, only 20% of all in-situ precipitation events were correctly detected by CHIRPS with no effect of topography found on detection skill performance. This research could be valuable for decision-makers in dryland regions (as well as the Barada Basin) for water resource planning and drought early warning systems using CHIRPS.

One of the most often-used parameters that describes morphology and runoff from a watershed is the time of concentration (Tc). At gauged watersheds, Tc can be determined using rainfall and a runoff hydrograph, while for ungauged watersheds, empirical equations are used. A good initial estimate of Tc greatly improves the accuracy of runoff predictions. In our study, we applied 14 empirical equations to determine Tc. Tarján Creek, which is located in northeastern Hungary, was selected as the trial gauged watershed. It is located in a mountainous region with an area of 72 km². The input parameters for the empirical equations were determined using geoinformatical tools. To evaluate the accuracy of the empirical equations, HEC-HMS was used to model the runoff. Using the measured runoff data, both continuous and event-based models were calibrated. For direct runoff, Clark’s unit hydrograph was selected. Tc is one of the input parameters for this model. After the calibration, the estimates from the empirical equations for Tc were compared to the HEC-HMS calibrated values for each subwatershed. The empirical estimates varied greatly. The Wisnovszky-equation, which is most often used in Hungary, underestimated Tc.

Iraq has faced escalating water scarcity over the past two decades, driven by climate change, upstream water withdrawals, and prolonged economic instability. These factors have caused deterioration in irrigation systems, inefficient water distribution, and growing social unrest. As per capita water availability falls below critical levels, Iraq is entering a period of acute water stress. This escalating water scarcity directly impacts water and food security, public health, and economic stability. This study aims to develop a general framework combining decision support systems (DSSs) with Integrated Comprehensive Water Management Strategies (ICWMSs) to support water planning, allocation, and response to ongoing water scarcity and reductions in Iraq. Implementing such a system is essential for Iraq to alleviate its continuing severe situation and adequately tackle its worsening water scarcity that has intensified over the years. This integrated approach is fundamental for enhancing planning efficiency, improving operational performance and monitoring, optimizing water allocation, and guiding informed policy decisions under scarcity and uncertainty. The current study highlights various international case studies that show that DSSs integrate real-time data, artificial intelligence, and advanced modeling to provide actionable policies for water management. Implementing such a framework is crucial for Iraq to mitigate this critical situation and effectively address the escalating water scarcity. Furthermore, Iraq’s water management system requires modifications considering present and expected future challenges. This study analyzes the inflows of the Tigris and Euphrates rivers from 1933 to 2022, revealing significant reductions in water flow: a 31% decrease in the Tigris and a 49.5% decline in the Euphrates by 2021. This study highlights the future 7–20% water deficit between 2020 and 2035. Furthermore, this study introduces a flexible, tool-based framework supported by a DSS with the DPSIR model (Driving Forces, Pressures, State, Impacts, and Responses) designed to address and reduce the gap between water availability and increasing demand. This approach proposes a multi-hazard risk matrix to identify and prioritize strategic risks facing Iraq’s water sector. This matrix links each hazard with appropriate DSS-based response measures and supports scenario planning under the ICWMS framework. The proposed framework integrates hydro-meteorological data analysis with hydrological simulation models and long-term investment strategies. It also emphasizes the development of institutional frameworks, the promotion of water diplomacy, and the establishment of transboundary water allocation and operational policy agreements. Efforts to enhance national security and regional stability among riparian countries complement these actions to tackle water scarcity effectively. Simultaneously, this framework offers a practical guideline for water managers to adopt the best management policies without bias or discrimination between stakeholders. By addressing the combined impacts of anthropogenic and climate change, the proposed framework aims to ensure rational water allocation, enhance resilience, and secure Iraq’s water strategies, ensuring sustainability for future generations.

More frequent high-intensity, short-duration rainfall events increase the risk of flash floods on steeply sloped watersheds. Where measured data are unavailable, numerical models emerge as valuable tools for predicting flash floods. Recent applications of various hydrological and hydrodynamic models to predict overland flow have highlighted the need for improved representations of the complex flow processes that are inherent in flash floods. This study aimed to identify an optimal modeling approach for characterizing leaf litter losses during flash floods. At a gauged watershed in the Hidegvíz Valley in Hungary, a physical-based model was calibrated using two distinct rainfall–runoff events. Two modeling methodologies were implemented, integrating canopy interception and leaf litter storage, to understand their contributions during flash flood events. The results from the model’s calibration demonstrated this approach’s effectiveness in determining the impact of leaf litter on steep-sloped watersheds. Soil parameters can estimate the behavior of leaf litter during flash flood events. In this study, hydraulic conductivity and initial water content emerged as critical factors for effective parametrization. The findings underscore the potential of a hydrodynamic model to explore the relationship between leaf litter and flash flood events, providing a framework for future studies in watershed management and risk-mitigation strategies.

The western shoreline of the Danube from Érd to Mohács consists of loess bluffs up to 50 m high. These bluffs can be susceptible to landslides when groundwater conditions weaken the supporting loess. Often this will occur during periods of high rainfall, however morphological, geological and other factors are also important in triggering these movements. Changes in pore water pressures related to precipitation, confined water levels driven by remote catchments, and river level fluctuations are widely recognized as important factors controlling the loess bank stability. This work aims to determine the interaction of rainfall, river level, drainage and local pumping on the pore pressure regime and stability of the bluffs. As a first step, a realistic 2-dimensional infiltration and groundwater model was built that reflects the influence of river levels, rainfall patterns, and local pumping. Based on model results, initial and boundary conditions have a strong influence on seasonal pore pressures. Further study will better define those influences on slope stability along the bluffs.