Open Access Editorial Special Issue

Open Access Original Research Article - Special Issue

Impact Assessment of Hydrology and Water Quality in the Saugahatchee Creek under Projected Land Use and Climate Change Scenarios Using WARMF

Sushban Shrestha, Xing Fang, Rajesh Sawant, Luke J. Marzen

International Journal of Environment and Climate Change, Page 360-388
DOI: 10.9734/BJECC/2014/11559

The hydrology and water quality of a stream or reservoir can be affected due to rapid urbanization and land use change in its watershed. Climate change, if it occurs, is likely to have additional impacts on hydrology and water quality of the watershed system. In this study, a watershed model WARMF (Watershed Analysis Risk Management Framework) was applied to the Saugahatchee Creek Watershed which includes two stream branches that were listed on State of Alabama’s 303(d) list of impaired water for nutrients and organic enrichment/dissolved oxygen. WARMF model for the Saugahatchee Creek Watershed was developed and model calibration and validation were performed. The model was then used to investigate hydrologic and water quality response to two different land use scenarios (LU 2009 and LU 2030) and four statistically downscaled future climate scenarios derived from Canadian Global Coupled Model (CGCM3) and Hadley Centre Coupled Climate Model (HadCM3). Temperature, dissolved oxygen, total nitrogen, total phosphorus, and algal concentration were the water quality parameters simulated along with flow. Based on monthly average of daily predicted values, the effect due to land use change was not significant except for nutrient concentration. The monthly average of daily total phosphorus concentration for LU 2030 is predicted to increase up to 72% more than baseline (LU 2009) under past climate conditions (1981–2010). Based on model results, the monthly average of daily surface water temperature is predicted to rise for all future climate scenarios. The monthly average of daily flow is predicted to increase corresponding to CGCM3 (annual average increase of 88%) and decrease corresponding to HadCM3 scenarios (annual average decrease of -49%). Accordingly, nutrient concentration is expected to decrease corresponding to CGCM3 and increase corresponding to HadCM3 scenarios. DO concentration are predicted to fall up to 2.3 mg/l (monthly average), especially in summer for the four climate scenarios. Combined land use and climate change scenarios cause the increase in nutrient concentrations for future land use and climate scenarios (e.g., annual TP from 0.082 mg/l for the baseline to 0.203 mg/l for HadCM3 A2 20s scenario). Chlorophyll-a concentration during the growing season is expected to increase to 25.8 and 26.3 μg/l under HadCM3 A2 and B2 scenarios due to combined effect, respectively, in comparison to 18 μg/l for the baseline (1981–2010 and LU2009). The results of this study can be incorporated into watershed management and planning strategies.

Open Access Original Research Article - Special Issue

Stream Flow Response to Skilled and Non-linear Bias Corrected GCM Precipitation Change in the Wami River Sub-basin, Tanzania

Frank Joseph Wambura

International Journal of Environment and Climate Change, Page 389-408
DOI: 10.9734/BJECC/2014/13457

The reliability of stream flow projection under changing climate cannot be guaranteed if the General Circulation Model (GCM) used for the projection of future climate does not predict well its past climate. In this study stream flows in the Wami River sub-basin were simulated under changing climate by the skilled and non-linear bias corrected GCM using a physically based and semi distributed rainfall runoff model, SWAT. The SWAT model was setup using the terrain, land use, soil, precipitation and temperature data. The baseline water uses were used to naturalise stream flows and the SWAT model was calibrated and validated using the historical stream flows. In addressing future runoff projections the domestic, livestock, irrigation and industrial water demands in the sub-basin were projected to the year 2039 using the current irrigation area growth rates, Tanzania vision 2025 and development plans for the Wami River sub-basin. The GCMs were incorporated in the hydrological model so as to factor in the effects of climate change. Precipitation was selected as the changing climatic variable for projection because runoff is very sensitive to precipitation as compared to other climatic variables like temperature. A total of twenty four GCMs from CMIP3 database representing twentieth century precipitation were interpolated into forty five sub-catchments in the sub-basin and evaluated for their skills. The HADCM3 model was selected due to its highest skill score in predicting past climate. Then the HADCM3 precipitation signal of scenario A2, was corrected by Non-linear Bias Correction (NBC) in the forty five sub-catchments in the sub-basin and used to simulate future stream flow. The results of stream flow simulated using skilled and non-linear corrected HADCM3 precipitation signal shows that stream flow is projected to increase for the near term climatology (2010 – 2039).

Open Access Original Research Article - Special Issue

Climate Impact on Freshwater Biodiversity: General Patterns in Extreme Environments of North-Eastern Siberia (Russia)

Sophia Barinova, Viktor Gabyshev, Olga Gabysheva

International Journal of Environment and Climate Change, Page 423-443
DOI: 10.9734/BJECC/2014/9530

Aims: The aims of the current study are to reveal the response of high latitude riverine planktonic algal communities in northeastern Siberia to extreme climatic conditions of its habitats.
Study Design: We implemented diverse statistical methods, which represent some new approaches in freshwater algal diversity analysis.
Place and Duration of Study: Institute of Evolution, University of Haifa, Israel, Institute for Biological Problems of Cryolithozone SB RAS, Russia, between June 2008 and January 2014.
Methodology: We collected 800 samples of phytoplankton from 400 sites of 12 northeastern Siberian rivers in gradients of climatic and chemical variables that we analyzed. New indices - Geo-associated and Dynamic Habitat Index were included in this analysis. Statistical methods for comparative floristic analyses were used for calculating the similarity of algal communities among the sampling stations. Multiple regression stepwise statistical analysis on phytoplankton including chemical and climatic variables data was performed. Species diversity in algal communities and their environmental variables relationships were calculated. 
Results: As a result, 1283 species (1637 taxa of species and infraspecies) from six taxonomic divisions were identified in phytoplankton communities. Species richness as a whole increased to the north. Abundance and biomass were highly correlated. Two types of phytoplankton communities were identified: a southern community with increasing diatoms and a northern group with decreasing diatoms to the north. Diatoms prevailed but were replaced by green algae in high mountains or by green and Chrysophyta algae and Cyanobacteria in the Arctic. We revealed major variables that considered stimulating or stress factors with helps of statistical prorgams.
Conclusion: Statistical analyses of phytoplankton in 12 large rivers revealed an increase in species richness to the north with community structure changing under stimulation of air temperature, ice-free periods, humidity, and trophic variables were stimulants and water transparency and speed flow were considered stress factors.

Open Access Original Research Article

Monitoring Spatial and Temporal Seaweeds Variation Using Remote Sensing Data in Al-Shoaiba Coast, Red Sea

Gihan A. El Shoubaky, Mona F. Kaiser

International Journal of Environment and Climate Change, Page 409-422
DOI: 10.9734/BJECC/2014/10034

Aims: Spatial variability and temporal dynamics of benthic seaweeds using the field investigation and Landsat Thematic Mapper images
Place and Duration of Study: Al-Shoaiba area, Saudi Arabia, Red Sea was investigated and the study area was divided into four sites extending about 10 km. The study period extended seasonally from summer 2011 to spring 2012.
Methodology: The assessment of seaweeds abundance and distribution were performed using quadrate method. Methodology includes analyses of the Enhanced Landsat Thematic Mapper (ETM+) images.
Results: A total of 46 seaweed taxa were collected from Al-Shoaiba region belonging to three different algal phyla to extend on reef flat to hundreds of yards to open sea. The field observations showed the broad macroalgal groups as optically mixture. The main confusion was distinguished between macroalgal groups. The contribution of seaweeds varied significantly not only between seasons, but also between sites. The physical parameters showed a close relationship between air and sea water temperatures. Generally, the weather tends to be warm at the selected sites. The pH values were slightly alkaline. Water salinity was relatively high especially in summer and autumn. Diverse of macroalgal communities was shown pronounced seasonal changes. Image classifications of remote sensing data showed large visual appearance of algal vegetation in summer and autumn on the reef flat than in winter and spring. High temperature and evaporation during summer and autumn may causes decline in sea water level. In contrary, low temperature leads to increasing the sea water level to cover most of the reef flat in winter and spring. 
Conclusion: This study emphasizes the significant impact of seasonal variations, especially temperature, on the spatial and temporal distribution of seaweeds in Al- Shoaiba coast, Saudi Arabia, Red Sea.

Open Access Original Research Article

Simulation and Validation of Cisco Habitat in Minnesota Lakes Using the Lethal-Niche-Boundary Curve

Xing Fang, Liping Jiang, Peter C. Jacobson, Nancy Z. Fang

International Journal of Environment and Climate Change, Page 444-470
DOI: 10.9734/BJECC/2014/11482

Fish survival in lakes is strongly influenced by water temperature and dissolved oxygen (DO) concentration. A one-dimensional (vertical) lake water quality model MINLAKE 2012 was calibrated in 23 Minnesota lakes and used to simulate daily water temperature and DO concentrations in 36 representative lake types under past (1992–2008) climate conditions and a future climate scenario (MIROC 3.2). The 36 representative Minnesota lake types were developed based on three maximum depths (Hmax = 4, 13, and 24 m), three surface areas (As = 0.2, 1.7, 10 km2), and four Secchi depths (SD = 1.2, 2.5, 4.5, and 7 m, from eutrophic to oligotrophic lake). A fish habitat model using the lethal-niche-boundary curve of adult cisco (Coregnous artedi, a cold-water fish species) was then developed to evaluate cisco oxythermal habitat and survival in Minnesota lakes.The fish habitat model was validated in the 23 Minnesota lakes of which 18 had cisco mortality while 5 had no cisco mortality in the unusually warm summer of 2006. Cisco lethal and habitable conditions in the 23 lakes simulated by the model had anoverall good agreement with observations in 2006. After model validation, cisco lethal days in the 36 lake types were modeled using simulated daily temperature and DO profiles from MINLAKE2012. Polymictic shallow lakes with lake geometry ratio As0.25/Hmax> 5.2 m-0.5 were simulated to typically not support cisco oxythermal habitat under past climate conditions and the future climate scenario. Medium-depth lakes are projected to be most vulnerable to climate warming with most increase in the number of years with cisco kill (average increase 13 years out of 17 simulation years). Strongly stratified mesotrophic and oligotrophic deep lakes are possible to support cisco habitat under both past and future climate conditions, and these deep lakes are good candidates for cisco refuge lakes that should be protected against water quality deteriorations.