The global solar radiation estimation and analysis of solar energy: Case study for Osmaniye,Turkey

This paper investigates the prediction of solar radiation model and actual solar energy in Osmaniye, Turkey. Four models were used to estimate using the parameters of sunshine duration and average temperature. In order to obtain the statistical performance analysis of models, the coefficient of determination (R²), mean absolute percentage error (MAPE), mean absolute bias error (MABE), and root mean square error (RMSE) were used. Results obtained from the linear regression using the parameters of sunshine duration and average temperature showed a good prediction of the monthly average daily global solar radiation on a horizontal surface. In order to obtain solar energy, daily and monthly average solar radiation values were calculated from the five minute average recorded values by using meteorological measuring device. As a result of this measurement, the highest monthly and yearly mean solar radiation values were 698 (April in 2013) and 549 (2014 year) W/m² respectively. On an annual scale the maximum global solar radiation changes from 26.38 MJ/m²/day by June to 19.19 MJ/m²/day by September in 2013. Minimum global solar radiation changes from 14.05 MJ/m²/day by October to 7.20 MJ/m²/day by January in 2013. Yearly average energy potential during the measurement period was 16.53 MJ/m²/day (in 2013). The results show that Osmaniye has a considerable solar energy potential to produce electricity.     

Performance of a small-scale solar-powered adsorption cooling system

In this study, an experimental investigation on the performance of a small-scale residential-size solar-driven adsorption (silica gel-water) cooling system that was constructed at Assiut University campus, Egypt is carried out. As Assiut area is considered as hot, arid climate, field tests for performance assessment of the system operation during the summer season are performed under different environmental operating conditions. The system consists of an evacuated tube with a reflective concentration parabolic surface solar-collector field with a total area of 36 m², a silica gel-water adsorption chiller of 8 kW nominal cooling capacity, and hot and cold water thermal storage tanks of 1.8 and 1.2 m³ in volume, respectively. The results of summer season field test show that under daily solar insolation varying from 21 to 27 MJ/m², the solar collectors employed in the system had high and almost constant thermal efficiency. The daily solar-collector efficiency during the period of system operation ranged from about 50% to 78%. The adsorption chiller performance shows that the chiller average daily coefficient of performance (COP) was 0.41 with the average cooling capacity of 4.4 kW when the cooling-water and chilled-water temperatures were about 31°C and 19°C, respectively. As the chiller cooling water is cooled by the cooling tower in the hot arid area, the cooling water is at a higher temperature than the design point of the chiller. Therefore, an experiment was carried out using the city water for cooling. The results show that an enhancement in the chiller COP by 40% and the chilling power by 17% has been achieved when the city water was 27.7°C.     

Global solar radiation and energy yield estimation from photovoltaic power plants for small loads

Daily global solar radiation on a horizontal surface and duration of sunshine hours have been determined experimentally for five meteorological stations in Saudi Arabia, namely, Abha, Al-Ahsa, Al-Jouf, Al-Qaisumah, and Wadi Al-Dawaser sites. Five-years of data covering 1998–2002 period have been used. Suitable Angstrom models have been developed for the global solar radiation estimation as a function of the sunshine duration for each respective sites. Daily averages of monthly solar PV power outputs have been determined using the Angstrom models developed. The effect of the PV cell temperature on the PV efficiency has been considered in calculating the PV power output. The annual average PV output energy has been discussed in all five sites for small loads. The minimum and maximum monthly average values of the daily global solar radiation are found to be 12.09 MJ/m²/d and 30.42 MJ/m²/d for Al-Qaisumah and Al-Jouf in the months of December June, respectively. Minimum monthly average sunshine hours of 5.89 hr were observed in Al-Qaisumah in December while a maximum of 12.92 hr in Al-Jouf in the month of June. Shortest range of sunshine hours of 7.33–10.12 hr was recorded at Abha station. Minimum monthly average Solar PV power of 1.59 MJ/m²/day was obtained at Al-Qaisumah in the month of December and a maximum of 3.39 MJ/m²/day at Al-Jouf in June. The annual PV energy output was found to be 276.04 kWh/m², 257.36 kWh/m², 256.75 kWh/m², 245.44 kWh/m², and 270.95 kWh/m² at Abha, Al-Ahsa, Al-Jouf, Al-Qaisumah, and Wadi Al-Dawaser stations, respectively. It is found that the Abha site yields the highest solar PV energy among the five sites considered.     

EVAPOTRANSPIRATION MEASUREMENTS AND MODELING FOR THREE WETLAND SYSTEMS IN SOUTH FLORIDA1

ABSTRACT: At the Everglades Nutrient Removal project in south Florida, three lysimeters were installed to measure daily evapotranspiration (ET) rates from cattails (Typha domingensis), mixed marsh vegetation, and an open water/algae system. The cattail lysimeter began operation in February 1993. The mixed marsh vegetation lysimeter began operation in January 1994, and the open water lysimeter with occasional algae cover began operation in December 1993. The mean measured ET rate was 3.6 mm, 3.5 mm, and 3.7 mm per day for the cattail, mixed marsh vegetation, and open water/algae system, respectively. High resolution weather data were continuously measured at the site. Six models were applied to estimate daily ET rates of the three systems. The Penman-Monteith equation best estimated ET of cattail and mixed marsh vegetation, and the Penman Combination equation was most suitable for the open water/algae system. Empirical equations based on solar radiation and maximum temperature produced estimates of daily ET from the three systems that are comparable to models that require many more parameters. In cases where limited data is available, the calibrated simple models can be used to estimate ET from wetlands in south Florida.     

Spatiotemporal Evaluation of Simulated Evapotranspiration and Streamflow over Texas Using the WRF‐Hydro‐RAPID Modeling Framework

This study assesses a large‐scale hydrologic modeling framework (WRF‐Hydro‐RAPID) in terms of its high‐resolution simulation of evapotranspiration (ET) and streamflow over Texas (drainage area: 464,135 km²). The reference observations used include eight‐day ET data from MODIS and FLUXNET, and daily river discharge data from 271 U.S. Geological Survey gauges located across a climate gradient. A recursive digital filter is applied to decompose the river discharge into surface runoff and base flow for comparison with the model counterparts. While the routing component of the model is pre‐calibrated, the land component is uncalibrated. Results show the model performance for ET and runoff is aridity‐dependent. ET is better predicted in a wet year than in a dry year. Streamflow is better predicted in wet regions with the highest efficiency ~0.7. In comparison, streamflow is most poorly predicted in dry regions with a large positive bias. Modeled ET bias is more strongly correlated with the base flow bias than surface runoff bias. These results complement previous evaluations by incorporating more spatial details. They also help identify potential processes for future model improvements. Indeed, improving the dry region streamflow simulation would require synergistic enhancements of ET, soil moisture and groundwater parameterizations in the current model configuration. Our assessments are important preliminary steps towards accurate large‐scale hydrologic forecasts.     

EVAPOTRANSPIRATION AND CANOPY RESISTANCE AT AN UNDEVELOPED PRAIRIE IN A HUMID SUBTROPICAL CLIMATE1

ABSTRACT: Reliable estimates of evapotranspiration from areas of wildland vegetation are needed for many types of water-resource investigations. However, little is known about surface fluxes from many areally important vegetation types, and relatively few comparisons have been made to examine how well evapotranspiration models can predict evapotranspiration for soil-, climate-, or vegetation-types that differ from those under which the models have been calibrated. In this investigation at a prairie site in west-central Florida, latent heat flux (λE) computed from the energy balance and alternatively by eddy covariance during a 15-month period differed by 4 percent and 7 percent on hourly and daily time scales, respectively. Annual evapotranspiration computed from the energy balance and by eddy covariance were 978 and 944 mm, respectively. An hourly Penman-Monteith (PM) evapotranspiration model with stomatal control predicated on water-vapor-pressure deficit at canopy level, incoming solar radiation intensity, and soil water deficit was developed and calibrated using surface fluxes from eddy covariance. Model-predicted λE agreed closely with λE computed from the energy balance except when moisture from dew or precipitation covered vegetation surfaces. Finally, an hourly PM model developed for an Amazonian pasture predicted λE for the Florida prairie with unexpected reliability. Additional comparisons of PM-type models that have been developed for differing types of short vegetation could aid in assessing interchangeability of such models.     

Using LiDAR Data Analysis to Estimate Changes in Insolation Under Large‐Scale Riparian Deforestation1

Greenberg, Jonathan Asher, Erin L. Hestir, David Riano, George J. Scheer, and Susan L. Ustin, 2012. Using LiDAR Data Analysis to Estimate Changes in Insolation Under Large‐Scale Riparian Deforestation. Journal of the American Water Resources Association (JAWRA) 48(5): 939‐948. DOI: 10.1111/j.1752‐1688.2012.00664.x Abstract: Riparian vegetation provides shade from insolation to stream channels. A consequence of removing vegetation may be an increase in insolation that can increase water temperatures and negatively impact ecosystem health. Although the mechanisms of riparian shading are well understood, spatially explicit, mechanistic models of shading have been limited by the data requirements of precisely describing the three‐dimensional structure of a riparian corridor. Remotely acquired, high spatial resolution LiDAR data provide detailed three‐dimensional vegetation structure and terrain topography over large regions. By parameterizing solar radiation models that incorporate terrain shadowing with LiDAR data, we can produce spatially explicit estimates of insolation. As a case study, we modeled the relative change in insolation on channels in the Sacramento‐San Joaquin River Delta under current conditions and under a hypothesized deforested Delta using classified LiDAR, rasterized at a 1‐m resolution. Our results suggest that the removal of levee vegetation could result in a 9% increase in solar radiation incident on Delta waters, and may lead to water temperature increases. General, coarse‐scale channel characteristics (reach width, azimuth, levee vegetation cover, and height) only accounted for 72% of the variation in the insolation. This indicates that the detailed information derived from LiDAR data has greater explanatory power than coarser reach‐scale metrics often used for insolation estimates.     

Assessment of Alternative Methods for Statistically Downscaling Daily GCM Precipitation Outputs to Simulate Regional Streamflow

This study applied three statistical downscaling methods: (1) bias correction and spatial disaggregation at daily time scale (BCSD_daily); (2) a modified version of BCSD which reverses the order of spatial disaggregation and bias correction (SDBC), and (3) the bias correction and stochastic analog method (BCSA) to downscale general circulation model daily precipitation outputs to the subbasin scale for west‐central Florida. Each downscaled climate input dataset was then used in an integrated hydrologic model to examine differences in ability to simulate retrospective streamflow characteristics. Results showed the BCSD_daily method consistently underestimated mean streamflow because the highly spatially correlated small precipitation events produced by this method resulted in overestimation of evapotranspiration. Highly spatially correlated large precipitation events produced by the SDBC method resulted in overestimation of the standard deviation of wet season daily streamflow and the magnitude/frequency of high streamflow events. BCSA showed better performance than the other methods in reproducing spatiotemporal statistics of daily precipitation and streamflow. This study demonstrated differences in statistical downscaling techniques propagate into significant differences in streamflow predictions, and underscores the need to carefully select a downscaling method that reproduces precipitation characteristics important for the hydrologic system under consideration.     

Estimation of Evapotranspiration Across the Conterminous United States Using a Regression With Climate and Land‐Cover Data1

Sanford, Ward E. and David L. Selnick, 2012. Estimation of Evapotranspiration Across the Conterminous United States Using a Regression with Climate and Land‐Cover Data. Journal of the American Water Resources Association (JAWRA) 1‐14. DOI: 10.1111/jawr.12010 Abstract: Evapotranspiration (ET) is an important quantity for water resource managers to know because it often represents the largest sink for precipitation (P) arriving at the land surface. In order to estimate actual ET across the conterminous United States (U.S.) in this study, a water‐balance method was combined with a climate and land‐cover regression equation. Precipitation and streamflow records were compiled for 838 watersheds for 1971‐2000 across the U.S. to obtain long‐term estimates of actual ET. A regression equation was developed that related the ratio ET/P to climate and land‐cover variables within those watersheds. Precipitation and temperatures were used from the PRISM climate dataset, and land‐cover data were used from the USGS National Land Cover Dataset. Results indicate that ET can be predicted relatively well at a watershed or county scale with readily available climate variables alone, and that land‐cover data can also improve those predictions. Using the climate and land‐cover data at an 800‐m scale and then averaging to the county scale, maps were produced showing estimates of ET and ET/P for the entire conterminous U.S. Using the regression equation, such maps could also be made for more detailed state coverages, or for other areas of the world where climate and land‐cover data are plentiful.     

Enhanced solar still productivity using transparent walls with an integral trough and organic porous absorber material

This experimental work has been conducted to compare the performance of the modified stills with that of the conventional still. Three modified stills (S1, S2, and S3) and conventional still (S4) were fabricated, each with 0.5 m² of the basin area. S1 and S3 had transparent double glass walls with air in between acting as insulation, whereas S2 has a single transparent wall. S4 has insulated plywood walls painted black from inside. A mixture of coco peat and charcoal was used in S1, S2, and S3, whereas there was no basin material for S4. Experiments were conducted by changing the water quantity in the solar still ranging from 5 to 10 kg. Maximum distillate output of 5.46 l/m²-d was obtained for S2, whereas it was 3.80 l/m²-d for S4 for an average solar radiation intensity of 675 W/m² (24.3 MJ/m²-d). Use of transparent walls with troughs to collect condensate increased the condenser area by 78.4%. The distillate water cost per liter was estimated as Rs. 0.86 (0.013 US$) and Rs. 1.61 (0.025 US$) for S2 and S4, respectively. Energy payback time for S2 was estimated as 4 months. Theoretical and experimental values showed that there is a significant loss of incoming solar radiation due to wall shadow.     

Assessing Satellite and Ground‐Based Potential Evapotranspiration for Hydrologic Applications in the Colorado River Basin

This study evaluates a remotely sensed and two ground‐based potential evapotranspiration (PET) products for hydrologic application in the Upper Colorado River Basin (UCRB). The remotely sensed Moderate Resolution Imaging Spectroradiometer product (MODIS‐PET) is a continuous, daily time series with 250 m resolution derived using the Priestley‐Taylor (P‐T) equation. The MODIS‐PET is evaluated against regional flux tower data as well as a synthetic pan product (Epan; 0.125°, daily) derived from the North American Land Data Assimilation System (NLDAS) and a Hargreaves PET derived from DAYMET variables (DAYMET‐PET; 1 km, daily). Compared to point‐scale PET computed using regional flux tower data, the MODIS‐PET had lower errors, with RMSE values ranging from 2.24 to 2.85 mm/day. Epan RMSE values ranged from 3.70 to 3.76 mm/day and DAYMET‐PET RMSE values ranged from 3.55 to 4.58 mm/day. Further investigation showed biases in temperature and radiation data contribute to uncertainty in the MODIS‐PET values, while bias in NLDAS temperature, downward shortwave (SW↓), and downward longwave (LW↓) propagate in the Epan estimates. Larger discrepancies between methods were observed in the warmer, drier regions of the UCRB, however, the MODIS‐PET was more responsive to landcover transitions and better captured basin heterogeneity. Results indicate the satellite‐based MODIS product can serve as a viable option for obtaining spatial PET values across the UCRB.     

A Simple Process‐Based Snowmelt Routine to Model Spatially Distributed Snow Depth and Snowmelt in the SWAT Model1

Abstract: We present a method to integrate a process‐based (PB) snowmelt model that requires only daily temperature and elevation information into the Soil and Water Assessment Tool (SWAT) model. The model predicts the spatiotemporal snowpack distribution without adding additional complexity, and in fact reduces the number of calibrated parameters. To demonstrate the utility of the PB model, we calibrate the PB and temperature‐index (TI) SWAT models to optimize agreement with stream discharge on a 46‐km² watershed in northwestern Idaho, United States, for 10 individual years and use the calibrated parameters for the year with the best agreement to run the model for 15 remaining years. Stream discharge predictions by the PB and TI model were similar, although the PB model simulated snowmelt more accurately than the TI model for the remaining 15‐year period. Spatial snow distributions predicted by the PB model better matched observations from LandSat imagery and a SNOTEL station. Results for this watershed show that including PB snowmelt in watershed models is feasible, and calibration of TI‐based watershed models against discharge can incorrectly predict snow cover.     

Evaluation of various global solar radiation models for Nigeria

This study assessed the performance of six solar radiation models. The objective was to determine the most accurate model for estimating global solar radiation on a horizontal surface in Nigeria. Twenty-two years meteorological data sets collected from the Nigerian Meteorological agency and the National Aeronautics and Space Administration for the three regions, covering the entire climatic zones in Nigeria were utilized for calibrating and validating the selected models for Nigeria. The accuracy and applicability of various models were determined for three locations (Abuja, Benin City, and Sokoto), which spread across Nigeria using seven viable statistical indices. This study found that the estimation results of considered models are statistically significant at the 95% confidence level, but their accuracy varies from one location to another. However, the multivariable regression relationship deduced in terms of sunshine ratio, air temperature ratio, maximum air temperature, and cloudiness performs better than other relationships. The multivariable relationship has the least root mean square error and mean absolute bias error, not exceeding 1.0854 and 0.8160 MJ m^?2 day^?1, respectively, and monthly relative percentage error in the range of ± 12% for the study areas.     

Estimating Water Budgets and Vertical Leakages for Karst Lakes in North‐Central Florida (United States) Via Hydrological Modeling1

Lin, Zhulu, 2011. Estimating Water Budgets and Vertical Leakages for Karst Lakes in North‐Central Florida (United States) Via Hydrological Modeling. Journal of the American Water Resources Association (JAWRA) 1‐16. DOI: 10.1111/j.1752‐1688.2010.00513.x Abstract: Newnans, Lochloosa, and Orange Lakes are closely hydrologically connected karst lakes located in north‐central Florida, United States. The complex karst hydrology in this region poses a great challenge to the hydrological modeling that is essential to the development of Total Maximum Daily Loads for these lakes. We used a Hydrological Simulation Program – Fortran model coupled with the parallel Parameter ESTimation model calibration and uncertainty analysis software to estimate effectively the hydrological interactions between the lakes and the underlying upper Floridan aquifer and the water budgets for these three lakes. The net results of the lake‐groundwater interactions in Newnans and Orange Lakes are that both lakes recharge the underlying upper Floridan aquifer, with the recharge rate of the latter one magnitude greater than that of the former. However, for Lochloosa Lake, the net lake‐groundwater interaction is that the lake gains water from groundwater in a significant amount, approximately 40% of its total terrestrial water input. The annual average vertical leakages estimated for Newnans, Lochloosa, and Orange Lakes are 6.0 × 10⁶, ?8.9 × 10⁶, and 44.4 × 10⁶ m³, respectively. The average vertical hydraulic conductance (K_v/b) of the units between a lake bottom and the underlying upper Floridan aquifer in this region are also estimated to be from 1.26 × 10^?4 to 1.01 × 10^?3 day^?1.     

Validation of Satellite Precipitation Adjustment Methodology From Seven Basins in the Continental United States1

Tobin, Kenneth J. and Marvin E. Bennett, 2012. Validation of Satellite Precipitation Adjustment Methodology From Seven Basins in the Continental United States. Journal of the American Water Resources Association (JAWRA) 48(2): 221‐234. DOI: 10.1111/j.1752‐1688.2011.00604.x Abstract: The precipitation science community has expressed concern regarding the ability of satellite‐based precipitation products to accurately capture rainfall values over land. There has been some work that has focused on addressing the deficiencies of satellite precipitation products, particularly on the adjustment of bias. This article outlines a methodology that adjusts satellite products utilizing ground‐based precipitation data. The approach is not a simple bias adjustment, but is a three‐step process that transforms a satellite product based on a ground‐based precipitation product (NEXRAD‐derived Multisensor Precipitation Estimator [MPE] product or rain‐gauge data). The developed methodology was successfully applied to seven moderate‐to‐large sized watersheds from continental United States (CONUS) and northern Mexico over a spectrum of climatic regimes ranging from dry to humid settings. Methodology validation is based on comparison of observed and simulated streamflow generated with SWAT (Soil and Water Assessment Tool) model using unadjusted and adjusted precipitation products as input. Streamflow comparison is based on mass balance error and Nash‐Sutcliffe efficiency coefficient. Finally, the contribution of how adjustment to correct misses, false alarms, and bias impacts adjusted datasets and the potential impact that the adjustment methodology can have on hydrological applications such as water resource monitoring and flood prediction are explored.     

Assessment of Future Climate Change Impact on Water Quality of Chungju Lake,South Korea,Using WASP Coupled with SWAT

This study is to evaluate the future potential impact of climate change on the water quality of Chungju Lake using the Water Quality Analysis Simulation Program (WASP). The lake has a storage capacity of 2.75 Gm³, maximum water surface of 65.7 km², and forest‐dominant watershed of 6,642 km². The impact on the lake from the watershed was evaluated by the Soil and Water Assessment Tool (SWAT). The WASP and SWAT were calibrated and validated using the monthly water temperatures from 1998 to 2003, lake water quality data (dissolved oxygen, total nitrogen [T‐N], total phosphorus [T‐P], and chlorophyll‐a [chl‐a]) and daily dam inflow, and monthly stream water quality (sediment, T‐N, and T‐P) data. For the future climate change scenario, the MIROC3.2 HiRes A1B was downscaled for 2020s, 2050s, and 2080s using the Change Factor statistical method. The 2080s temperature and precipitation showed an increase of +4.8°C and +34.4%, respectively, based on a 2000 baseline. For the 2080s watershed T‐N and T‐P loads of up to +87.3 and +19.6%, the 2080s lake T‐N and T‐P concentrations were projected to be 4.00 and 0.030 mg/l from 2.60 and 0.016 mg/l in 2000, respectively. The 2080s chl‐a concentration in the epilimnion and the maximum were 13.97 and 52.45 μg/l compared to 8.64 and 33.48 μg/l in 2000, respectively. The results show that the Chungju Lake will change from its mesotrophic state of 2000 to a eutrophic state by T‐P in the 2020s and by chl‐a in the 2080s. Editor's note: This paper is part of a featured series on Korean Hydrology. The series addresses the need for a new paradigm of river and watershed management for Korea due to climate and land use changes.     

Feasibility Assessment of Basin Solar Stills

The present study assesses the feasibility of exploiting single- and double-basin solar stills in our daily lives. An investigation is carried out to determine the thermal performance and economic viability of making use of solar stills in water desalination. The climatic conditions of Tehran (35°44?N, 51°30?E) are considered to assess the feasibility of the basins. Transient energy and mass balance equations are utilized for modeling the thermal performance. The equations are solved by using fourth-order Runge–Kutta method in FORTRAN. The daily productivities of single- and double-basin solar stills are found to be 5.22 kg/m² and 7.73 kg/m², respectively, while the effect of different water masses (20–100 kg) on the productivity of each system was found to be optimum at 20 kg/m². The results are compared with experimental work performed under different climatic conditions to examine the validity of the feasibility of basins in general. A life cycle cost analysis performed for Tehran, yields that single- and double-basin solar stills have savings-to-investment ratios of 4.2 and 4.8, respectively, indicating that they are economically feasible.     

Real‐Time Analysis of Energy Generation of a Photovoltaic System Installed in the City of Lajeado,Rio Grande do Sul

Considering successive and costly increases in electricity rates, this article evaluates the generation of electricity from a photovoltaic system using solar energy, a renewable source. The solar photovoltaic system is installed at UNIVATES University Center, a public university in the state of Rio Grande do Sul, Brazil, and it is also connected to the electrical grid. Data related to the climatic conditions of the location, such as incident solar radiation, rainfall, and mean temperature, were obtained during the system's evaluation period and used along with bibliographic research on similar systems installed in southern Brazil. Our study quantified the energy produced over one calendar year (2014) and related it to the climatic variables and the conversion efficiency achieved by the system's photovoltaic modules. Our results show that there is both a strong relationship between the production of energy and climatic conditions and that the city, Lajeado, and the Brazilian state of Rio Grande do Sul, have good potential to supply energy using photovoltaic systems connected to the electrical grid. The horizontal global solar radiation average obtained in the study location was 4.14 kilowatts per square meter per day (kWh/m²/day), and the average monthly production of energy reached 243.93 kWh/m²/month, with a total of 2,927.10 kWh produced in 2014, achieving a monthly average conversion efficiency of 11.07%. This conversion efficiency is close to the value of 12.6% obtained in 2013 in a similar study of the same solar photovoltaic system conducted over a shorter time period.     

Impacts of Climate Change on Hydrology and Water Resources in the Boise and Spokane River Basins1

Jin, Xin and Venkataramana Sridhar, 2012. Impacts of Climate Change on Hydrology and Water Resources in the Boise and Spokane River Basins. Journal of the American Water Resources Association (JAWRA) 48(2): 197‐220. DOI: 10.1111/j.1752‐1688.2011.00605.x Abstract: In the Pacific Northwest, warming climate has resulted in a lengthened growing season, declining snowpack, and earlier timing of spring runoff. This study characterizes the impact of climate change in two basins in Idaho, the Spokane River and the Boise River basins. We simulated the basin‐scale hydrology by coupling the downscaled precipitation and temperature outputs from a suite of global climate models and the Soil and Water Assessment Tool (SWAT), between 2010 and 2060 and assess the impacts of climate change on water resources in the region. For the Boise River basin, changes in precipitation ranged from ?3.8 to 36%. Changes in temperature were expected to be between 0.02 and 3.9°C. In the Spokane River region, changes in precipitation were expected to be between ?6.7 and 17.9%. Changes in temperature appeared between 0.1 and 3.5°C over a period of the next five decades between 2010 and 2060. Without bias‐correcting the simulated streamflow, in the Boise River basin, change in peak flows (March through June) was projected to range from ?58 to +106 m³/s and, for the Spokane River basin, the range was expected to be from ?198 to +88 m³/s. Both the basins exhibited substantial variability in precipitation, evapotranspiration, and recharge estimates, and this knowledge of possible hydrologic impacts at the watershed scale can help the stakeholders with possible options in their decision‐making process.     

Rain Water Harvesting in Bermuda1

Rowe, Mark P., 2011. Rain Water Harvesting in Bermuda. Journal of the American Water Resources Association (JAWRA) 47(6):1219–1227. DOI: 10.1111/j.1752‐1688.2011.00563.x Abstract: Roof‐top rain water harvesting is mandated by law for all buildings in Bermuda and is the primary source of water for domestic supply. The average rate at which rain water is harvested at the typical house with four occupants is, however, insufficient to meet average demand. While just over one‐third of households have access to supplementary water either from mains pipelines or private wells, the majority rely on deliveries from water “truckers” (tankers) to augment their rain water supply. Assuming a reasonably constant daily demand, there is a linear relationship between the “maximum optimum capacity” of a water storage tank and the size of the rain water catchment area, which depends on the characteristics of the rainfall at a given geographic location. A simple spreadsheet model was developed to simulate tank storage levels for various combinations of catchment area, tank capacity, and demand, with an input of actual daily rainfall data for a study period of nearly three years. It was found that for typical cycles of rainfall surpluses and deficits in Bermuda, the tank capacity which there is no benefit in exceeding — the “optimum maximum capacity”— is 0.37 m³ of storage capacity per 1 m² of catchment area. Furthermore, it was concluded that many domestic water storage tanks in Bermuda are larger than necessary, especially so where there is a significant imbalance between rain water supply and demand.