A global dynamic runoff application and dataset based on the assimilation of GPM, SMAP, and GCN250 curve number datasets.

Runoff modelling is a crucial element in hydrologic sciences. However, a global runoff database is not currently available at a resolution higher than 0.1°. We use the recently developed Global Curve Number dataset (GCN250) to develop a dynamic runoff application (2015 - present) and that can be accessed via a Google Earth Engine application. We also provide a global mean monthly runoff dataset for April 2015-2021 in GeoTIFF format at a 250-meter resolution. We utilize soil moisture and GPM rainfall to dynamically retrieve the appropriate curve number and generate the corresponding runoff anywhere on Earth. Mean annual global runoff ratio results for 2021 were comparable to the runoff ratio from the Global Land Data Assimilation System (0.079 vs. 0.077, respectively). Mean annual global runoff from GCN and GLDAS were within 11% each other for 2020-2021 (0.18 vs. 0.16 mm/day, respectively). The GCN250 runoff application and the dataset are useful for many water applications such hydrologic design, land management, water resources management, and flood risk assessment.

Nationwide Assessment of Water Quality in Rivers across Lebanon by Quantifying Fecal Indicators Densities and Profiling Antibiotic Resistance of Escherichia coli.

The use of contaminated water has been associated with severe disease outbreaks. Due to widespread pollution with untreated sewage, concerns have been raised over water quality in Lebanon, a country with well-documented challenges in infrastructure. Here, we evaluated the water quality of major rivers in Lebanon by quantifying the densities of fecal indicator bacteria (fecal coliforms and Escherichia coli). Additionally, we assessed the dissemination of antibiotic-resistant E. coli in river water. Composite water samples (n = 132) were collected from fourteen rivers, and 378 E. coli were isolated and analyzed. Fecal coliforms and E. coli were detected in 96.29% and 95.5% of the samples, respectively. Additionally, 73.48-61.3% and 31.81% of the samples exceeded the microbiological acceptability standards for irrigation and the fecal coliform limit for recreational activities, respectively. The E. coli exhibited resistance to ampicillin (40% of isolates), amoxicillin + clavulanic acid (42%), cefepime (4%), cefotaxime (14%), cefalexin (46%), cefixime (17%), doripenem (0.3%), imipenem (0.5%), gentamicin (6%), kanamycin (9%), streptomycin (35%), tetracycline (35%), ciprofloxacin (10%), norfloxacin (7%), trimethoprim-sulfamethoxazole (32%), and chloramphenicol (13%). Notably, 45.8% of the isolates were classified as multidrug resistant (MDR). Our results highlight the need to urgently address fecal pollution and the dissemination of antibiotic resistance in Lebanese rivers.

Refugees, water balance, and water stress: Lessons learned from Lebanon.

The Syrian crisis caused a massive influx of displaced people into neighboring countries, with Lebanon hosting the highest per capita number of refugees (3:10). Water remains the most critical natural resource that influences the resilience of host and refugee communities. We provide a new GIS-based updated water balance and water scarcity analysis at the national and the watershed level in Lebanon by comparing current conditions to no-refugee levels. Results show a small (6%) increase in water stress in an average water year at the national level that masks hot spots of water scarcity at the local geography. While domestic water use increased by 20%, we find that refugees' water use is only 10% of agricultural water use in summer. We also show that interventions to rehabilitate the water networks can reduce water stress to better than pre-conflict levels (3% less stress).

Data set on current and future crop suitability under the Representative Concentration Pathway (RCP) 8.5 emission scenario for the major crops in the Levant, Tigris-Euphrates, and Nile Basins.

This article describes crop suitability maps (raster data) for thirty five crops in the Jordan, Litani, Orontes, Nile, and Tigris-Euphrates river basins. Spatial data on crop suitability are provided for two periods: current conditions as the average of the years 1970-2000, and projected future conditions for the year 2050 as an average for the years 2041-2060. The data were generated by simulating mean monthly climatic data from the Coupled Model Intercomparison Project Phase 5 (CMIP5). These climatic data are downscaled to the 1-km scale from the Intergovernmental Panel on Climate Change 5th Assessment Report. Mean monthly climatic datasets from the WorldClim database were used to generate the suitability datasets using the FAO EcoCrop model under the Representative Concentration Pathway (RCP) 8.5 emission scenario for three General Circulation Models: CCSM4, GFDL-CM3, and HadGEM2-ES with a spatial resolution of 30 arc-seconds. The findings reveal that many crops in the Levant will witness a decrease in their suitability, whereas suitability of crops in the upper Nile Basin will increase by 2050.

Dataset used for assessing animal and poultry production water footprint in selected countries of the MENA region.

This article describes the data used to assess and quantify the local and imported (green, blue, and grey) fractions of unit and total water footprint of six categories of livestock animals along with their derived products in 14 selected countries of the MENA region. Interpretation of this data can be found in a research article titled "New estimates of water footprint for animal products in fifteen countries of the Middle East and North Africa (2010-2016)" [1]. These countries are Algeria, Egypt, Israel, Jordan, Kuwait, Lebanon, Mauritania, Morocco, Oman, Qatar, Saudi Arabia, Tunisia, Turkey, and Yemen. The main farm animals covered are beef cattle, dairy cows, sheep and goats, broilers, and layers. These data cover the period 2010-2016. The data show that the MENA region consumes more than 80 billion m3 of water every year for animal consumption, most of which is imported. The proportion of imported blue water to total imported water is higher than that of the local.

GCN250, new global gridded curve numbers for hydrologic modeling and design.

The USDA curve-number (CN) method is fundamental for rainfall-runoff modeling. A global CN database is not currently available for geospatial hydrologic analysis at a resolution higher than 0.1°. We developed a globally consistent, gridded dataset defining CNs at the 250 m spatial resolution from new global land cover (300 m) and soils data (250 m). The resulting data product - GCN250 - represents runoff for a combination of the European space agency global land cover dataset for 2015 (ESA CCI-LC) resampled to 250 m and geo-registered with the hydrologic soil group global data product (HYSOGs250m) released in 2018. Our analysis indicated that medium to high runoff potential currently dominates the globe, with curve numbers ranging between 75 and 85. Global curve numbers were 62, 78, and 90 for dry, average, and wet antecedent runoff conditions, respectively. Australia has the highest runoff potential, while Europe has the lowest. Runoff ratios compare well with GLDAS. The potential application of this data includes hydrologic design, land management applications, flood risk assessment, and groundwater recharge modeling.