Freshwater scarcity in Halabja, Iraqi Kurdistan, is exacerbated by climate change, urbanization, and population growth, leading to increased stormwater runoff and groundwater contamination. This study aims to identify optimal locations for low-impact development (LID) systems, specifically bioswales and bioretention areas, as sustainable solutions for managing urban stormwater and improving water quality. The Best Management Practices (BMPs) siting tool, developed by the United States Environmental Protection Agency (USEPA), was utilized in this study within ArcMap GIS software to conduct a comprehensive analysis. Several environmental and infrastructural layers were extracted, including roads, slope, soil type, hydrologic soil group, groundwater depth, and land use. Additionally, an Analytical Hierarchy Process (AHP) model was used to map groundwater potential, utilizing six weighted factors. The BMPs tool identified 599 LID-suitable sites across the 22 km² area, with overlap between bioswale and bioretention due to similar design criteria. Results indicate that only 20% of the area has excellent groundwater potential, 4.67% has good potential, 33.84% shows moderate potential, while 58.44% exhibits poor potential. These findings underscore the crucial need for stormwater harvesting strategies to offset inadequate groundwater reserves, thereby supporting resilient urban water management through eco-friendly infrastructure

Background: Phlebotomus papatasi is known as the main vector of zoonotic cutaneous leishmaniasis. This study aimed to investigate the effect of geographical and bioclimatic factors on the Ph. papatasi distribution. Methods: A total of 34 villages were selected, and sampling was performed three times using 120 sticky traps in each selected village. All the collected species were mounted and identified. The densities of Ph. papatasi were measured in all the villages and entered ArcMap as a point layer. The required bioclimatic and environmental variables were extracted from the global climate database and The normalized difference vegetation index was obtained from the MODIS satellite imagery, also, all variables entered into ArcMap as raster layers, so The numerical value of each independent variable in the cell where the selected village is located in this, was extracted using spatial analyst tools and the value to point submenu. All the data were finally entered IBM SPSS, and the relationship was examined between the number of collected Ph. papatasi and the independent variables using Spearman’ s correlation test. Results: A total of 1773 specimens of Ph. papatasi were collected. The findings of this study showed that max temperature of the warmest month, temperature annual range, temperature seasonality, mean diurnal range, precipitation seasonality, mean temperature of the driest and warmest quarter were positively associated with the density of Ph. papatasi. Conclusion: Air temperature and precipitation were shown as the most significant factors in the distribution of Ph. papatasi.

Background: Phlebotomus papatasi is known as the main vector of zoonotic cutaneous leishmaniasis. This study aimed to investigate the effect of geographical and bioclimatic factors on the Ph. papatasi distribution. Methods: A total of 34 villages were selected, and sampling was performed three times using 120 sticky traps in each selected village. All the collected species were mounted and identified their species. The densities of Ph. papatasi were measured in all the villages and entered into ArcMap as a point layer. The required bioclimatic and environmental vari-ables were extracted from the global climate database and The normalized difference vegetation index was obtained from the MODIS satellite imagery, also, all variables entered into ArcMap as raster layers, so The numerical value of each independent variable in the cell where the selected village is located in this, was extracted using spatial analyst tools and the value to point submenu. All the data were finally entered into IBM SPSS, and the relationship was exam-ined between the number of collected Ph. papatasi and the independent variables using Spearman's correlation test. Results: A total of 1773 specimens of Ph. papatasi were collected. The findings of this study showed that max tem-perature of warmest month, temperature annual range, temperature seasonality, mean diurnal range, precipitation sea-sonality, mean temperature of driest and warmest quarter were positively associated with the density of Ph. papatasi. Conclusion: Air temperature and precipitation were shown as the most significant factors in the distribution of Ph. pa-patasi.

Landslide zoning is one of the tools that can be used to identify unstable slopes and use them in sustainable development programs. In this study, to assess the relative risk of slopes and estimate the experimental probability of landslides in the Bababozorg Basin, we used nine factors affecting the slope, including slope degree, slope direction, height, lithology, land use type, precipitation, and distances from faults, communication lines and water supply network. Then we made a map for each factor. We also identified and recorded the landslides in the basin and prepared a map of the landslides. By plotting the factors influencing the slope, with the landslide distribution map, and using the LNRF (Landslide Nominical Risk Factor) model in the ArcMap software environment, the effect of each factor on the slope status was estimated. Accordingly, 6. 42%, 17. 87, 27. 13, 27. 45 and 21. 11% of the area were classified as very low, low, medium, high and very high, respectively.