https://jwhr.birjand.ac.ir/ Water Harvesting Research en daily 1 Sun, 01 Mar 2026 00:00:00 +0330 Sun, 01 Mar 2026 00:00:00 +0330 https://jwhr.birjand.ac.ir/article_3903.html This research investigates the trends and changes in the statistical distribution of climatic parameters (the warm days index, TX90p, and precipitation) and hydrological parameters (river flow discharge) in the Maroun basin over a 50-year period (1971-2020). The Mann-Kendall test was employed to identify trends, and the Pettitt test was used to determine the timing of abrupt changes. The results indicated that the TX90p index exhibits a statistically significant increasing trend (p-value = 0.018), with a change point in the year 1995, following which its mean value increased by 57%. Although the decreasing trends in precipitation and discharge were not statistically significant at the 95% level, the Pettitt test identified an abrupt change in both parameters in the year 2008. A comparison of the statistical distribution of the data before and after the change points, using Kolmogorov-Smirnov, analysis of variance, and location tests, confirmed that not only the central tendency but also the shape and dispersion of these parameters have changed significantly. Specifically, the mean precipitation and discharge decreased by 28% and 46%, respectively, while their standard deviations also decreased by 38% and 52%, respectively. These findings collectively indicate a shift in the regional climate pattern towards warmer and drier conditions, which has serious implications for water resources management. https://jwhr.birjand.ac.ir/article_3919.html  This study presents a comprehensive unsteady-state mathematical model for analyzing heat and mass transfer processes in a tubular solar still (TSS), aimed at enhancing the accuracy of temperature predictions and freshwater productivity assessments. The model incorporates time-dependent energy balance equations for key components—including the saline water, trough, humid air, and transparent cover—while accounting for convective, evaporative, radiative, and condensative heat transfer mechanisms. Assumptions such as uniform water temperature, negligible vapor leakage, saturated vapor near the water surface, and minimal solar absorption by humid air are employed to simplify the analysis. Mass transfer coefficients are derived from established correlations, and natural convection is modeled using Rayleigh and Grashof numbers for curved surfaces. Simulations under constant solar radiation (750 W/m²) and ambient temperature (28°C) reveal that the trough exhibits the highest temperature (up to 60°C), followed by saline water, humid air, and the cover (lowest at ~40°C), with all components stabilizing after approximately 2 hours. Cumulative distillate yield reaches approximately 0.5 kg after 8 hours of operation. Parametric analyses demonstrate that a 2.5-fold increase in solar radiation intensity results in a 3.4-fold rise in productivity, while enlarging the diameter from 0.1 m to 0.4 m yields a 4.5-fold enhancement, though at increased cost. The model provides valuable insights for optimizing TSS designs in water-scarce regions, highlighting the potential for sustainable, low-cost desalination.  https://jwhr.birjand.ac.ir/article_3921.html Monitoring the surface area of reservoirs is crucial for effective water resource management, particularly in arid and semi-arid regions where water availability fluctuates significantly. This study utilizes Sentinel-2 imagery to assess water extent variations in the Latyan Dam reservoir in Iran from 2016 to 2024. By applying three well-established water indices—NDWI, MNDWI, & AWEIsh—water surface areas were delineated. Sentinel-2 Level-2A images, preprocessed using the Sen2Cor algorithm, were analyzed in SNAP software, ensuring high accuracy in atmospheric correction and reflectance values. The derived water area was validated using index intersection and union approaches to refine detection accuracy. The reservoir’s surface area showed a clear declining trend, decreasing from 3.3 km² in 2016 (wettest year) to 1.1 km² in 2023 (driest year), corresponding to a shrinkage of about 2.2 km². Throughout 2016–2024, the uncertainty band between the union and intersection of NDWI, MNDWI, and AWEIsh remained relatively narrow, fluctuating between approximately 0.2 and 0.4 km², with slightly lower values in drier years. Applying Otsu thresholding substantially increased the number of uncertain water pixels compared to the fixed global threshold (index ≥ 0), from 3446 to 8250 pixels in 2016 and from 1718 to 7191 pixels in 2023, indicating that the global threshold provides more stable and conservative water detection for long‑term monitoring. This approach provides an efficient, replicable methodology for large-scale water monitoring, supporting sustainable water resource management and policy decisions. https://jwhr.birjand.ac.ir/article_3977.html Water scarcity poses a significant challenge in semi-arid regions, with climate variability and growing demand exacerbating the strain on traditional water sources. As a contribution to sustainable water solution in a dryland region, this study reports the potential harvest from rooftop catchments in a populated built environment using Kenyatta University, Kitui Campus, in Kenya, as a case study. Roof catchment areas were computed using standard GIS procedures. Mean monthly rainfall was established using rainfall trends from 1981–2024. Estimated harvestable water was calculated standard formula for volume, but discounted for expected evaporation and seepage loses using applicable runoff coefficients. Results show that the entire campus can collect at least 11 million litres annually, with institutional buildings contributing 7.8 million litres and the staff quarters 3.4 million litres per year. With a population of about 1000 people coupled with water use efficiency, the campus can operate within a water secure scenario throughout the year. Seasonal analysis reveals that the October–December provides 361 mm of rainfall twice the volume of the March–May (MAM) which is 176 mm, necessitating strategic storage solutions to bridge dry periods. Based on the cost factor of above ground plastic tanks, this study proposes decentralized rainwater harvesting systems combining a series of large-capacity residential tanks available on the market (30,000-50,000 litres) for high-yield buildings and smaller tanks (5,000–20,000 litres) per individual residential houses. Lessons from this paper offer Kitui Campus, other learning environments, and households with ridged roof catchments, significantly opportunities through enhanced public health performance indicators and irrigation agriculture. https://jwhr.birjand.ac.ir/article_4007.html One of the hydrological phenomena with a very complex nature is the flood phenomenon, which causes a lot of damage if it occurs. In this study, the joint frequency analysis of flood characteristics at the Sepid Dasht-Zaz station in the Dez basin, Iran, over a 30-year period was investigated using nested copula functions. For this purpose, the flood characteristics such as peak flow, flood volume and base time of the flood were used. By fitting 11 different distribution functions to the studied series, finally, based on statistical tests, the generalized extreme value distribution (GEV) was chosen as a suitable marginal distribution for the studied variables. After selecting the marginal distribution, Archimedean family copulas (including Frank, Ali-Mikhail-Haq, and Clayton) were used for joint frequency analysis of the paired flood characteristics (peak flow and flood volume, peak flow and time base and flood volume and time base). The results showed that Frank and Clayton for the mentioned pair-variables are most consistent with the empirical copulas. The joint return period was used to investigate the trivariate return period of events. The results of joint analysis of flood characteristics in the study area resulted in the typical return period curves for Sepid Dasht-Zaz, which provides the return period of each flood characteristic with different probabilities and given by other flood characteristics. Since the characteristics of floods are different in each flood event, univariate flood analysis does not take into account all characteristics, and hence the use of nested copulas by increasing dimension of analysis can provide more realistic results.  https://jwhr.birjand.ac.ir/article_4051.html Rooftop gardening has become popular in many regions of the world, yet its adoption in Bangladesh remains limited due to several challenges. Urban households often avoid rooftop cultivation because of concerns such as over-irrigation causing waterlogging, the structural threat of water accumulation on roofs, and the inconvenience of frequently climbing stairs to water plants. These factors collectively discourage broader participation in rooftop agriculture despite its environmental and socio-economic benefits. To overcome these barriers, this study introduces a sensor-based automatic drip irrigation system designed to optimize water use, reduce manual labor, and ensure safe rooftop gardening. The research evaluated a rain sensor-based automatic drip irrigation system in comparison with customary watering system for tomato (Solanum lycopersicum L.) cultivation. The experiment was conducted at Sylhet Agricultural University from November 2024 to January 2025 following a Completely Randomized Design with two treatments: Sensor Based Automatic Drip Irrigation (SI) and Conventional Irrigation (CI) and five replications. The findings showed that the SI system significantly enhanced plant height, flower production, fruit yield, and total output relative to manual irrigation. Water use efficiency improved by 40%, with an overall 25% reduction in water application. Economic analysis showed that SI system was more profitable, with lower production costs (USD 55.10) compared to the CI system (USD 66.18). Overall, the findings indicate that sensor-based smart watering system offer a practical, cost-effective, and water-efficient solution for rooftop gardening in Bangladesh. By addressing limitations of manual irrigation, this technology can promote adoption of sustainable rooftop farming practices across the country. https://jwhr.birjand.ac.ir/article_4115.html Water erosion, especially in dry and semi-arid regions, is one of the most significant environmental challenges, playing a crucial role in the degradation of natural resources. Modeling tools such as RUSLE, in conjunction with GIS for spatial analysis and remote sensing, provide the ability to quantify and map erosion-prone areas. This study was conducted in the Sahlabad watershed to evaluate water erosion intensity and assess the influence of environmental factors, including rainfall erosivity, soil erodibility, topography, vegetation cover, and conservation practices. The RUSLE model was applied using meteorological data and spatial information derived from remote sensing and GIS techniques. Ultimately, water erosion intensity was classified into five categories: very low, low, moderate, high, and very high. The respective percentages for each category, from very low to very high erosion, were 79.49%, 0.95%, 8.83%, 10.21%, and 0.50%, respectively. The results highlight the importance of vegetation conservation and appropriate land management practices for reducing soil loss and protecting the Kaji Wetland. To reduce soil loss, preventing cultivation in vulnerable areas and planting Tamarix trees are recommended. https://jwhr.birjand.ac.ir/article_4230.html Drought risk assessment based on a reliable, integrated index that encompasses meteorological, hydrological, and agricultural dimensions is critical for understanding future drought trends and for implementing effective prevention and mitigation strategies. This study aims to develop a Multivariate Integrated Drought Index (MIDI) by combining four key drought indicators—Streamflow Drought Index (SDI), Standardized Runoff Index (SRI), Standardized Precipitation Index (SPI), and Standardized Precipitation-Evapotranspiration Index (SPEI)—to enable an objective and holistic evaluation of drought risk. The study area, the Sarbaz River Basin in southeastern Iran, is the region’s only permanent river system and holds strategic importance for agricultural development and unique ecological sustainability, particularly under escalating water scarcity driven by climate change and population growth. The MIDI was constructed using variable fuzzy set theory and the entropy weight method. Drought events were subsequently redefined in terms of duration and severity based on run theory. Copula functions were employed to model the joint probability distribution of drought duration and severity, allowing for a comprehensive assessment of drought risk. Results indicate that the MIDI is well correlated with the time series of individual meteorological and hydrological drought indices and demonstrates greater sensitivity and efficiency in capturing historical drought events compared to single indices. The Sarbaz River Basin has experienced over 100 drought events, with a mean duration of 2.21 months, and 94.6% of the events lasted fewer than five months, indicating that droughts in this basin tend to be of short duration yet occur with high frequency. Droughts of varying severity occur annually across the basin. Given this high frequency, it is recommended that water resource management plans incorporate the MIDI outputs and the joint duration–severity analysis to formulate proactive adaptation strategies. Future research should investigate the influence of climatic variables and land-use changes on drought dynamics within this critical basin. https://jwhr.birjand.ac.ir/article_4140.html Investigating climate change's impact on precipitation patterns using GCMs is crucial, but correcting their inherent biases is essential for reliable regional applications. The present study aimed to investigate the effect of seven bias correction methods and a weighted ensemble of the five best-corrected models on the accuracy of 14 CMIP6 models in predicting precipitation. Bias correction was performed for the baseline period 1990–2014, and the corrected outputs were validated against observational data from nine meteorological stations using RMSE, PBIAS, KGE, and NSE metrics. Based on the results, the ensemble method was selected as the superior approach at all stations, improving KGE from 0.54 to 0.56 (3.7%), improving NSE from 0.19 to 0.42 (121%), and reducing RMSE from 23.48 to 19.79 (15.7%). The ensemble reduced PBIAS at six stations (by ~77% on average. A one-tailed Wilcoxon signed-rank test confirmed that the superiority of the ensemble method is statistically significant (W = 45, n = 9, p = 0.0039). Among the individual methods, the Bernoulli gamma method, which is based on the separation of dry and wet days and the use of the gamma distribution, had the best performance. In the ensemble method, CESM2, CNRM-CM6-1, and MRI-ESM2-0 were consistently among the top five models at all stations. Precipitation projection using the optimal bias correction method (ensemble) and the best-performing CMIP6 model for the 2030–2055 period indicates that precipitation will decrease by an average of 10.46% under SSP1-2.6 (ranging from -6.1% to –13.7% across stations) and by an average of 14.6% under SSP5-8.5 (ranging from -9.2% to –18.7%). https://jwhr.birjand.ac.ir/article_4248.html Understanding the intricacies of regional climate change is essential for effective adaptation, yet trend analyses are often constrained by spatial aggregation biases. This study investigates the spatiotemporal evolution of maximum temperature in Lorestan Province, western Iran, over a 20-year period (2001–2020) by integrating conventional univariate trend detection with a novel multivariate approach based on Principal Component Analysis (PCA). Station-scale analysis using the modified Mann-Kendall test revealed a pervasive but largely non-significant positive annual warming trend across all eight stations, with total increases ranging from 0.77 °C to 1.25 °C. Crucially, monthly-scale disaggregation exposed a distinct seasonal asymmetry: significant warming was concentrated in February and the summer months (July–September), while transitional periods exhibited minimal change, demonstrating that annual aggregates conceal critical seasonal extremes. PCA revealed exceptional spatial coherence, with the first principal component explaining 99.9% of the total variance and factor loadings exceeding 0.999 across all stations, indicating a highly synchronized thermal regime governed by regional-scale drivers. However, the multivariate Mann-Kendall test found no significant region-wide trend (Z = 0.062, p = 0.951), highlighting that locally significant warming signals are diluted when spatially integrated, thereby cautioning against generalized regional policy. These findings underscore the necessity of local-scale trend assessments for climate adaptation, particularly in agriculture and water resources. The pronounced warming in February threatens plant chilling requirements, while intensifying summer heat elevates evapotranspiration and energy demands, necessitating targeted, site-specific management strategies rather than reliance on provincial averages for climate resilience planning in semiarid environments. https://jwhr.birjand.ac.ir/article_4244.html Water erosion in semi-arid mountain watersheds depends on both sediment-source potential and the structural connection of source areas to the drainage network. A multiannual, sensitivity-aware screening workflow was developed for the 105.20 km² Deli watershed, southwestern Iran, for 2005–2025. Landsat 5/7 indices were transformed to an Operational Land Imager-equivalent scale using local near-coincident Landsat 7–8 pairs, annual cover-management factors were derived, rainfall erosivity was represented using a CHIRPS–modified Fournier proxy, soil erodibility was estimated from SoilGrids, and topographic controls were derived from a 30 m DEM. Annual RUSLE products were combined with structural connectivity, hotspot persistence and conditional support-practice scenarios. The uncertainty measure is the low-to-high structural sensitivity range across alternative R, K, C and P assumptions, not a probabilistic confidence interval. All erosion and delivery results are unitless comparative index values rather than physical soil-loss or sediment-yield rates. The long-term mean potential soil-loss index was 582.11 index units; annual means ranged from 138.33 in 2010 to 1040.20 in 2018, with no significant monotonic watershed-scale trend. The annual response closely followed the rainfall-erosivity proxy (Spearman ρ = 0.98, p < 0.001), whereas its association with the watershed-mean C factor was weak and non-significant (ρ = −0.07, p = 0.758). Hotspots recurring in at least half of the years occupied 10.42 km², and mean relative structural uncertainty was 37.40%. Moderate and strong conditional P scenarios, representing 10–45% and 55–72.5% local reductions across eligible cells, lowered the index within 4.85 km² of stable cropland by 36.87% and 68.38%, but reduced the watershed-wide mean by only 0.34% and 0.63% because the treated domain covered about 4.6% of the watershed. The maps provide first-tier evidence for prioritizing field verification, monitoring and sediment pre-treatment. CHIRPS intensity limitations, the approximately 250 m support of SoilGrids and the absence of sediment observations preclude calibrated rates or stand-alone siting decisions. https://jwhr.birjand.ac.ir/article_4236.html Flood risk assessment in developing regions is often constrained by the absence of locally derived depth–damage functions, limiting the reliability of loss estimation and risk-informed planning. This study proposes an integrated methodology that combines the Source–Pathway–Receptor–Consequence (SPRC) framework with socio-economic indicators to assess fluvial flood risk in the Shotorak catchment, Qazvin Province, Iran. In the absence of local damage data, European Commission depth–damage curves were applied to hydraulic simulation outputs for 25- and 100-year return period flood events. The modelling results indicate maximum flood depths of 5.85 m and 11.02 m, with inundation extents of 29.79 ha and 45.67 ha, respectively. Residential land in Mohammadieh was affected over 3.4 ha under the 25-year scenario and 5.9 ha under the 100-year scenario, while agricultural land in Sharifieh experienced the greatest losses, increasing from 12.5 ha to 17.4 ha. Residential risk increased by 52% between the two scenarios, underscoring the exposure of expanding urban settlements. The findings reveal pronounced spatial variability in flood impact, driven by the interplay of topography, land use, and socio-economic conditions. Overall, the proposed framework offers a transferable and practical interim tool for flood risk screening and risk-sensitive planning in regions where local depth–damage functions are unavailable. https://jwhr.birjand.ac.ir/article_4243.html Sewer pipelines, as a critical urban infrastructure, are becoming a growing concern for managers as they approach the end of their service life. On the other hand, accessing and inspecting sewer pipelines using methods that involve human entry are problematic and high-risk. Current methods for assessing sewer pipelines utilize various types of equipment for condition inspection. One of the most widely used technologies for sewer pipeline inspection is video (CCTV) cameras. However, employing camera-based methods in extensive sewer networks requires licensed operators to review hours of video footage, which is time-consuming, labor-intensive, and prone to errors. In this study, the performance of two well-known convolutional neural network architectures, VGG16 and ResNet50, was compared for the automatic multi-label detection and classification of defects in sewer inspection video imagery. The proposed models were implemented on a subset of the public Sewer-ML dataset. In both models, a transfer learning approach was employed, with partial fine-tuning applied to the last deep block of the network, using ImageNet pre-trained weights. To address the severe class imbalance, class importance weighting was applied in the loss function, along with independent optimal thresholding for each class. The results show that ResNet50, with an F2CIW score of 61%, outperformed VGG16, which achieved 58%, and demonstrated superior performance in 12 out of the 17 defect classes. Given that ResNet50 achieved this performance with approximately one-fifth the number of parameters of VGG16, this architecture is introduced as a more suitable option for practical deployment in real-time sewer inspection monitoring systems. https://jwhr.birjand.ac.ir/article_4253.html The Astaneh–Kuchesfahan aquifer is a strategically important groundwater resource in northern Iran that has experienced progressive depletion due to climate variability, intensive abstraction, and hydrogeological heterogeneity. This study aimed to develop and calibrate a numerical groundwater flow model to assess aquifer behavior and evaluate management responses under future climate change scenarios. A three-layer MODFLOW model was constructed using drilling logs, hydrogeological surveys, and long-term observational data from 2000 to 2020, including groundwater levels, river discharge, precipitation, temperature, evapotranspiration, and hydrogeochemical records. Model calibration and sensitivity analysis were performed by adjusting key parameters such as horizontal and vertical hydraulic conductivity, storage coefficient, effective porosity, and recharge. Future simulations were conducted under RCP2.6, RCP4.5, and RCP8.5 climate pathways combined with management scenarios including abstraction reduction, optimized water allocation, artificial recharge, and integrated measures over 5-, 10-, and 20-year periods. The calibrated model reproduced groundwater-level dynamics with high accuracy (R² = 0.87–0.96, NSE = 0.89–0.96, RMSE < 0.30 m), while hydrogeochemical trends showed over 90% conformity with observed EC and TDS patterns. Results indicate that climate change is the dominant driver of long-term groundwater decline, with projected drawdown reaching 0.95 m and water-balance deficits increasing to 26.3 MCM under RCP8.5. Among management options, the integrated scenario performed best, reducing drawdown to 0.35 m and decreasing the deficit by more than 70%. The findings demonstrate that long-term integrated management is essential to enhance aquifer resilience and ensure sustainable groundwater use under increasing climatic stress. https://jwhr.birjand.ac.ir/article_4275.html Constant residuals commonly represent unresolved components of reservoir water balances, although their combined effects may vary with storage. This study investigated whether beginning-of-year storage explains annual water-balance residuals at Seymareh Dam, Iran, using inflow, outflow, and storage observations for 2011–2023. A linear storage-dependent residual was fitted using ordinary least squares and incorporated into the annual continuity equation. Parameter uncertainty and equifinality were examined through 10,000 Monte Carlo simulations within the Generalized Likelihood Uncertainty Estimation (GLUE) framework. Initial storage explained 32.3% of residual variability (R² = 0.323, p = 0.043). Compared with the no-loss baseline, the storage-dependent model improved in-sample Nash–Sutcliffe efficiency (0.5973 versus 0.3832) and reduced root mean square error (177.10 versus 219.17 MCM), although mean absolute error increased slightly. Using an NSE threshold of 0.50, 772 parameter sets (7.72%) were retained as behavioral. The resulting parameter-induced 95% prediction uncertainty envelope enclosed 9 of 13 observed annual storage changes (69.2%). Behavioral slope and intercept parameters were inversely correlated (r = −0.858), indicating equifinality. Leave-one-year-out refitting preserved the positive slope but did not establish independent predictive validity. The formulation offers a parsimonious diagnostic tool for long-term reservoir water-balance assessment, without resolving seasonal dynamics or individual physical loss processes.