Evaluation of Satellite‐Derived Rainfall Data for Multiple Physio‐Climatic Regions in the Santiago River Basin,Mexico

Assessment of water resources requires reliable rainfall data, and rain gauge networks may not provide adequate spatial representation due to limited point measurements. The Tropical Rainfall Measuring Mission (TRMM) provides rainfall data at global scale, and has been used with good results. However, TRMM data are an indirect measurement of rainfall, and therefore must be validated for its proper use. In this work, a validation scheme was designed and implemented to compare the TRMM Version 7 (V7) monthly rainfall product at different time frames with data measured in two hydrologic subregions of the Santiago River Basin (SRB) in Mexico: Río Alto Santiago and Río Bajo Santiago (RBS). Additionally, three physio‐climatic regions provide an assessment of the interplay of topography, distance from coastal regions, and seasonal weather patterns on the correspondence between both datasets. The TRMM V7 rainfall product exhibited good agreement with the rain gauge data particularly for the RBS and for the whole SRB during wettest summer and autumn seasons. However, strong regional dependence was observed due to differences in climate and topography. Overall, in spite of some noted underestimations, the monthly TRMM V7 rainfall product was found to provide useful information that can be used to complement limited monitoring as is the case of RBS. An improved combined rainfall product could be generated and thus gaining the most benefits from both data sources.     

Evaluation of the Global Precipitation Measurement (GPM) Satellite Rainfall Products over the Lower Colorado River Basin,Texas

Quality of precipitation products from the Integrated Multi‐satellitE Retrievals for Global Precipitation Measurement mission (IMERG) was evaluated over the Lower Colorado River Basin of Texas. Observations of several rainfall events of a wide range of magnitudes during May 2015 by a very dense network of 241 rain gauges over the basin were used as a reference. The impact of temporal and spatial downscaling of different satellite products (near/post‐real‐time) on their accuracy was studied. Generally, all IMERG products perform better when the temporal and spatial resolutions are downscaled. The Final product shows relatively better performance compared to the near‐real‐time products in terms of basic performance measures; however, regarding rainfall detection, all products show nearly similar performance. When considering rainfall detection, IMERG adequately captures the precipitation events; however, in terms of spatial patterns and accuracy, more improvements are needed. IMERG products analysis results may help developers gain insight into the regional performance of the product, improve the product algorithms, and provide information to end users on the products’ suitability for potential hydrometeorological applications. Overall, the IMERG products, even the uncalibrated product at its finest resolution, showed reasonable performance indicating their great potential for applications such as water resources management, prevention of natural disasters, and flood forecasting.     

EVALUATION OF NEXRAD STAGE III PRECIPITATION DATA OVER A SEMIARID REGION1

This study examines NEXRAD Stage III product (hourly, cell size 4 km by 4 km) for its ability in estimating precipitation in central New Mexico, a semiarid area. A comparison between Stage III and a network of gauge precipitation estimates during 1995 to 2001 indicates that Stage III (1) overestimates the hourly conditional mean (CM) precipitation by 33 percent in the monsoon season and 55 percent in the nonmonsoon season; (2) overestimates the hourly CM precipitation for concurrent radar‐gauge pairs (nonzero value) by 13 percent in the monsoon season and 6 percent in the nonmonsoon season; (3) overestimates the seasonal precipitation accumulation by 11 to 88 percent in monsoon season and underestimates by 18 to 89 percent in the nonmonsoon season; and (4) either overestimates annual precipitation accumulation up to 28.2 percent or underestimates it up to 11.9 percent. A truncation of 57 to 72 percent of the total rainfall hours is observed in the Stage III data in the nonmonsoon season, which may be the main cause for both the underestimation of the radar rainfall accumulation and the lower conditional probability of radar rainfall detection in the nonmonsoon season. The study results indicate that the truncation caused loss of small rainfall amounts (events) is not effectively corrected by the real‐time rain gauge calibration that can adjust the rainfall rates but cannot recover the truncated small rainfall events. However, the truncation error in the monsoon season may be suppressed due to the larger rainfall rate and/or combined effect of overestimates by bright band and hail contaminations, virga, advection, etc. In general, improvement in NEXRAD performance since the monsoon season in 1998 is observed, which is consistent with the systematic improvement in the NEXRAD network.     

Using SWAT to Model Streamflow in Two River Basins With Ground and Satellite Precipitation Data1

Abstract: Both ground rain gauge and remotely sensed precipitation (Next Generation Weather Radar – NEXRAD Stage III) data have been used to support spatially distributed hydrological modeling. This study is unique in that it utilizes and compares the performance of National Weather Service (NWS) rain gauge, NEXRAD Stage III, and Tropical Rainfall Measurement Mission (TRMM) 3B42 (Version 6) data for the hydrological modeling of the Middle Nueces River Watershed in South Texas and Middle Rio Grande Watershed in South Texas and northern Mexico. The hydrologic model chosen for this study is the Soil and Water Assessment Tool (SWAT), which is a comprehensive, physical‐based tool that models watershed hydrology and water quality within stream reaches. Minor adjustments to selected model parameters were applied to make parameter values more realistic based on results from previous studies. In both watersheds, NEXRAD Stage III data yields results with low mass balance error between simulated and actual streamflow (±13%) and high monthly Nash‐Sutcliffe efficiency coefficients (NS > 0.60) for both calibration (July 1, 2003 to December 31, 2006) and validation (2007) periods. In the Middle Rio Grande Watershed NEXRAD Stage III data also yield robust daily results (time averaged over a three‐day period) with NS values of (0.60‐0.88). TRMM 3B42 data generate simulations for the Middle Rio Grande Watershed of variable qualtiy (MBE = +13 to ?16%; NS = 0.38‐0.94; RMSE = 0.07‐0.65), but greatly overestimates streamflow during the calibration period in the Middle Nueces Watershed. During the calibration period use of NWS rain gauge data does not generate acceptable simulations in both watersheds. Significantly, our study is the first to successfully demonstrate the utility of satellite‐estimated precipitation (TRMM 3B42) in supporting hydrologic modeling with SWAT; thereby, potentially extending the realm (between 50°N and 50°S) where remotely sensed precipitation data can support hydrologic modeling outside of regions that have modern, ground‐based radar networks (i.e., much of the third world).     

Physically Based,Hydrologic Model Results Based on Three Precipitation Products1

Abstract: The main objective of the study is to examine the accuracy of and differences among simulated streamflows driven by rainfall estimates from a network of 22 rain gauges spread over a 2,170 km² watershed, NEXRAD Stage III radar data, and Tropical Rainfall Measuring Mission (TRMM) 3B42 satellite data. The Gridded Surface Subsurface Hydrologic Analysis (GSSHA), a physically based, distributed parameter, grid‐structured, hydrologic model, was used to simulate the June‐2002 flooding event in the Upper Guadalupe River watershed in south central Texas. There were significant differences between the rainfall fields estimated by the three types of measurement technologies. These differences resulted in even larger differences in the simulated hydrologic response of the watershed. In general, simulations driven by radar rainfall yielded better results than those driven by satellite or rain‐gauge estimates. This study also presents an overview of effects of land cover changes on runoff and stream discharge. The results demonstrate that, for major rainfall events similar to the 2002 event, the effect of urbanization on the watershed in the past two decades would not have made any significant effect on the hydrologic response. The effect of urbanization on the hydrologic response increases as the size of the rainfall event decreases.     

Rainfall Interception Based on Indirect Methods: A Case Study in Temperate Forests in Oaxaca,Mexico

Rainfall interception represents the amount of water trapped in natural cover that is not drained directly to the ground. Intercepted rainfall may evaporate after a rain event, making it one of the main drivers of water balance and hydrologic regionalization. This process can be affected by factors such as climate, altitude, vegetation type, and topography. Here is a simple method of calculating rainfall interception in temperate forests using in Santa Maria Yavesia, Oaxaca, and Mexico as an illustrative study area. We used two rain gauges to measure net precipitation (N_p) under the canopy at each study site and one gauge outside the canopy to obtain gross precipitation (G_p). Throughfall (T_h) was indirectly measured using hemispherical photographs. Rainfall interception was obtained through a combination T_h and G_p and N_p. The mean rainfall interception was 50.6% in the Abies forests, 23%–40% in the coniferous‐mixed forests, and 27.4% in the broad‐leaved forests. We classified rainfall events by intensity to determine the effect of canopy structure and precipitation and found that 75% of the events were weak events, 24% were moderate events, and 1% were strong events. In addition, we found that rainfall interception was lower when the intensity of precipitation was higher. Our method can be replicated in different ecosystems worldwide as a tool for assessing the influence of rainfall interception in terms of ecological services.     

Long‐Term High‐Resolution Radar Rainfall Fields for Urban Hydrology

Accurate records of high‐resolution rainfall fields are essential in urban hydrology, and are lacking in many areas. We develop a high‐resolution (15 min, 1 km²) radar rainfall data set for Charlotte, North Carolina during the 2001‐2010 period using the Hydro‐NEXRAD system with radar reflectivity from the National Weather Service Weather Surveillance Radar 1988 Doppler weather radar located in Greer, South Carolina. A dense network of 71 rain gages is used for estimating and correcting radar rainfall biases. Radar rainfall estimates with daily mean field bias (MFB) correction accurately capture the spatial and temporal structure of extreme rainfall, but bias correction at finer timescales can improve cold‐season and tropical cyclone rainfall estimates. Approximately 25 rain gages are sufficient to estimate daily MFB over an area of at least 2,500 km², suggesting that robust bias correction is feasible in many urban areas. Conditional (rain‐rate dependent) bias can be removed, but at the expense of other performance criteria such as mean square error. Hydro‐NEXRAD radar rainfall estimates are also compared with the coarser resolution (hourly, 16 km²) Stage IV operational rainfall product. Stage IV is adequate for flood water balance studies but is insufficient for applications such as urban flood modeling, in which the temporal and spatial scales of relevant hydrologic processes are short. We recommend the increased use of high‐resolution radar rainfall fields in urban hydrology.     

Drivers of future streamflow changes in watersheds across the Northeastern United States

Accurate projections of streamflow, which have implications for flooding, water resources, hydropower, and ecosystems, are critical to climate change adaptation and require an understanding of streamflow sensitivity to climate drivers. The northeastern United States has experienced a dramatic increase in extreme precipitation over the past 25 years; however, the effects of these changes, as well as changes in other drivers of streamflow, remain unclear. Here, we use a random forest model forced with a regional climate model to examine historical and future streamflow dynamics of four watersheds across the Northeast. We find that streamflow in the cold season (November–May) is primarily driven by 3-day rainfall and antecedent wetness (Antecedent Precipitation Index) in three rainfall-dominant watersheds, and 30-day rainfall, antecedent wetness, and 30-day snowmelt in the fourth, more snowmelt-dominated watershed. In the warm season (June–October), streamflow is driven by antecedent wetness and rainfall in all watersheds. By the end of the century (2070–2099), cold season streamflow depends on the importance placed on snow in the machine learning model, with changes ranging from −7% (with snow) to +40% (without snow) in a single watershed. Simulated future warm season streamflow increases in two watersheds (56% and 193%) due to increased precipitation and antecedent soil wetness, but decreases in the other two watersheds (−6% and −27%) due to reduced precipitation.     

Precipitation Extremes and Flood Frequency in a Changing Climate in Southeastern Virginia

Despite the advances in climate change modeling, extreme events pose a challenge to develop approaches that are relevant for urban stormwater infrastructure designs and best management practices. The study first investigates the statistical methods applied to the land‐based daily precipitation series acquired from the Global Historical Climatology Network‐Daily (GHCN‐D). Additional analysis was carried out on the simulated Multivariate Adaptive Constructed Analogs (MACA)‐based downscaled daily extreme precipitation of 15 General Circulation Models and Weather Research and Forecasting‐based hourly extreme precipitation of North American Regional Reanalysis to discern the return period of 24‐hr and 48‐hr events. We infer that the GHCN‐D and MACA‐based precipitation reveals increasing trends in annual and seasonal extreme daily precipitation. Both BCC‐CSM1‐1‐m and GFDL‐ESM2M models revealed that the magnitude and frequency of extreme precipitation events are projected to increase between 2016 and 2099. We conclude that the future scenarios show an increase in magnitudes of extreme precipitation up to three times across southeastern Virginia resulting in increased discharge rates at selected gauge locations. The depth‐duration‐frequency curve predicted an increase of 2–3 times in 24‐ and 48‐h precipitation intensity, higher peaks, and indicated an increase of up to 50% in flood magnitude in future scenarios.     

Trends in Raindrop Kinetic Energy with Modeled Climate Warming in the Lake Tahoe Basin

Two means by which climate change may increase surface soil erosion in mountainous terrain are: (1) increasing the frequency of extreme rainfall events and (2) decreasing the duration of snow cover on bare soil. We used output from four general circulation models (GCMs) and two greenhouse gas trajectories to produce a suite of hydrologic variables at a daily time‐step for historic and projected 21st Century conditions. We statistically disaggregated the daily rainfall to hourly, using hourly rainfall from a network of nine weather stations in the Tahoe Basin, and filtered out rain falling on a snowpack. We applied published equations to convert hourly intensity to raindrop kinetic energy (KE) for each day and grid cell in the Basin, averaged across grid cells, and created time series of total annual and maximum annual hourly kinetic energy (TKE and MKE) on snow‐free ground. Using the Generalized Extreme Value distribution, we calculated the significance of long‐term trends in KE on snow‐free ground, and estimated energy levels for return periods of 2, 20, and 100 years. We then detrended the snowpack data and compared the resulting trends in KE with the trends resulting from changes in both rainfall energy and snowpack under two GCMs. Principal findings include (1) upward trends in MKE, (2) stronger upward trends in TKE; and (3) an effect of increasing rainfall intensities on KE in some cases, and a strong effect of reduced snowpack in all cases examined.     

Precipitation Amount and Intensity Trends Across Southwest Saudi Arabia

This study examines precipitation accumulation and intensity trends across a region in southwest Saudi Arabia characterized by distinct seasonal weather patterns and mountainous terrain. The region is an example of an arid/semiarid area faced with maintaining sustainable water resources with a growing population. Annual and seasonal trends in precipitation amount were examined from 29 rain gages divided among four geographically unique regions from 1945/1946 to 2009. Two of the regions displayed significantly declining annual trends over the time series using a Mann‐Kendall test modified for autocorrelation (α < 0.05). Seasonal analysis revealed insignificant declining trends in at least two of the regions during each season. The largest and most consistent declining trends occurred during wintertime where all regions experienced negative trends. Several intensity metrics were examined in the study area from four additional stations containing daily data from 1985 to 2011. Intensity metrics included total precipitation, wet day count, simple intensity index, maximum daily annual rainfall, and upper/lower precipitation distribution changes. In general, no coherent trends were found among the daily stations suggesting precipitation is intensifying across the study area. The work represents the first of its size in the study area, and one of few in the region due to the lack of available long‐term data needed to properly examine precipitation changes.     

Rainfall conditions and rainwater harvesting potential in the urban area of Khartoum

Runoff water management is among the inherent challenges which face the sustainability of the development of arid urban centers. These areas are particularly at risk from flooding due to rainfall concentration in few heavy showers. On the other hand, they are susceptible to drought. The capital of Sudan (Khartoum) stands as exemplary for these issues. Hence, this research study aims at investigating the potential of applying rainwater harvesting (RWH) in Khartoum City Center as a potential urban runoff management tool. Rapid urbanization coupled with the extension of impervious surfaces has intensified the heat island in Khartoum. Consequently, increased frequency of heat waves and dust storms during the dry summer and streets flooding during the rainy season have led to environmental, economical, and health problems. The study starts with exposing the rainfall behavior in Khartoum by investigating rainfall variability, number of raindays, distribution of rain over the season, probability of daily rainfall, maximum daily rainfall and deficit/surplus of rain through time. The daily rainfall data show that very strong falls of >30 mm occur almost once every wet season. Decreased intra- and inter-annual rainfall surpluses as well as increased rainfall concentration in the month of August have been taking place. The 30-year rainfall variability is calculated at decade interval since 1941. Increasing variability is revealed with 1981–2010 having coefficients of variation of 66.6% for the annual values and 108.8–118.0% for the wettest months (July–September). Under the aforementioned rainfall conditions, this paper then explores the potential of RWH in Khartoum City Center as an option for storm water management since the drainage system covers only 40% of the study area. The potential runoff from the 6.5 km² center area is computed using the United States Natural Resources Conservation Services method (US-NRCS), where a weighted Curve Number (CN) of 94% is found, confirming dominant imperviousness. Rainfall threshold for runoff generation is found to be 3.3 mm. A 24,000 m³ runoff generated from a 13.1 mm rainfall (with 80% probability and one year return period) equals the drainage system capacity. An extreme rainfall of 30 mm produces a runoff equivalent to fourfold the drainage capacity. It is suggested that the former and latter volumes mentioned above could be harvested by applying the rational method from 18% and 80% rooftops of the commercial and business district area, respectively. Based on the above results, six potential sites can be chosen for RWH with a total roof catchment area of 39,558 m² and potential rooftop RWH per unit area of 0.033 m³. These results reflect the RWH potential for effective urban runoff management and better water resources utilization. RWH would provide an alternative source of water to tackle the drought phenomenon.     

Investigation of the Curve Number Method For Surface Runoff Estimation In Tropical Regions

This study tests the applicability of the curve number (CN) method within the Soil and Water Assessment Tool (SWAT) to estimate surface runoff at the watershed scale in tropical regions. To do this, surface runoff simulated using the CN method was compared with observed runoff in numerous rainfall‐runoff events in three small tropical watersheds located in the Upper Blue Nile basin, Ethiopia. The CN method generally performed well in simulating surface runoff in the studied watersheds (Nash‐Sutcliff efficiency [NSE] > 0.7; percent bias [PBIAS] < 32%). Moreover, there was no difference in the performance of the CN method in simulating surface runoff under low and high antecedent rainfall (PBIAS for both antecedent conditions: ~30%; modified NSE: ~0.4). It was also found that the method accurately estimated surface runoff at high rainfall intensity (e.g., PBIAS < 15%); however, at low rainfall intensity, the CN method repeatedly underestimated surface runoff (e.g., PBIAS > 60%). This was possibly due to low infiltrability and valley bottom saturated areas typical of many tropical soils, indicating that there is scope for further improvements in the parameterization/representation of tropical soils in the CN method for runoff estimation, to capture low rainfall‐intensity events. In this study the retention parameter was linked to the soil moisture content, which seems to be an appropriate approach to account for antecedent wetness conditions in the tropics.     

Nutrient and sediment concentrations and corresponding loads during the historic June 2008 flooding in eastern Iowa

A combination of above-normal precipitation during the winter and spring of 2007-2008 and extensive rainfall during June 2008 led to severe flooding in many parts of the midwestern United States. This resulted in transport of substantial amounts of nutrients and sediment from Iowa basins into the Mississippi River. Water samples were collected from 31 sites on six large Iowa tributaries to the Mississippi River to characterize water quality and to quantify nutrient and sediment loads during this extreme discharge event. Each sample was analyzed for total nitrogen, dissolved nitrate plus nitrite nitrogen, dissolved ammonia as nitrogen, total phosphorus, orthophosphate, and suspended sediment. Concentrations measured near peak flow in June 2008 were compared with the corresponding mean concentrations from June 1979 to 2007 using a paired t test. While there was no consistent pattern in concentrations between historical samples and those from the 2008 flood, increased flow during the flood resulted in near-peak June 2008 flood daily loads that were statistically greater (p < 0.05) than the median June 1979 to 2007 daily loads for all constituents. Estimates of loads for the 16-d period during the flood were calculated for four major tributaries and totaled 4.95 x 10(7) kg of nitrogen (N) and 2.9 x 10(6) kg of phosphorus (P) leaving Iowa, which accounted for about 22 and 46% of the total average annual nutrient yield, respectively. This study demonstrates the importance of large flood events to the total annual nutrient load in both small streams and large rivers.     

The Sensitivity of Northern Groundwater Recharge to Climate Change: A Case Study in Northwest Alaska1

Clilverd, Hannah M., Daniel M. White, Amy C. Tidwell, and Michael A. Rawlins, 2011. The Sensitivity of Northern Groundwater Recharge to Climate Change: A Case Study in Northwest Alaska. Journal of the American Water Resources Association (JAWRA) 47(6):1228–1240. DOI: 10.1111/j.1752‐1688.2011.00569.x Abstract: The potential impacts of climate change on northern groundwater supplies were examined at a fractured‐marble mountain aquifer near Nome, Alaska. Well water surface elevations (WSE) were monitored from 2004‐2009 and analyzed with local meteorological data. Future aquifer response was simulated with the Pan‐Arctic Water Balance Model (PWBM) using forcings (air temperature and precipitation) derived from fifth‐generation European Centre Hamburg Model (ECHAM5) global circulation model climate scenarios for extreme and modest increases in greenhouse gases. We observed changes in WSE due to the onset of spring snowmelt, low intensity and high intensity rainfall events, and aquifer head recession during the winter freeze period. Observed WSE and snow depth compared well with PWBM‐simulated groundwater recharge and snow storage. Using ECHAM5‐simulated increases in mean annual temperature of 4‐8°C by 2099, the PWBM predicted that by 2099 later freeze‐up and earlier snowmelt will decrease seasonal snow cover by one to two months. Annual evapotranspiration and precipitation are predicted to increase 27‐40% (55‐81 mm) and 33‐42% (81‐102 mm), respectively, with the proportion of snowfall in annual precipitation decreasing on average 9‐25% (p < 0.05). The amount of snowmelt is not predicted to change significantly by 2099; however, a decreasing trend is evident from 2060 in the extreme ECHAM5 greenhouse gas scenario. Increases in effective precipitation were predicted to be great enough to sustain sufficient groundwater recharge.     

Variable rainfall intensity and tillage effects on runoff, sediment, and carbon losses from a loamy sand under simulated rainfall

The low-carbon, intensively cropped Coastal Plain soils of Georgia are susceptible to runoff, soil loss, and drought. Reduced tillage systems offer the best management tool for sustained row crop production. Understanding runoff, sediment, and chemical losses from conventional and reduced tillage systems is expected to improve if the effect of a variable rainfall intensity storm was quantified. Our objective was to quantify and compare effects of a constant (Ic) intensity pattern and a more realistic, observed, variable (Iv) rainfall intensity pattern on runoff (R), sediment (E), and carbon losses (C) from a Tifton loamy sand cropped to conventional-till (CT) and strip-till (ST) cotton (Gossypium hirsutum L.). Four treatments were evaluated: CT-Ic, CT-Iv, ST-Ic, and ST-Iv, each replicated three times. Field plots (n=12), each 2 by 3 m, were established on each treatment. Each 6-m2 field plot received simulated rainfall at a constant (57 mm h(-1)) or variable rainfall intensity pattern for 70 min (12-run ave.=1402 mL; CV=3%). The Iv pattern represented the most frequent occurring intensity pattern for spring storms in the region. Compared with CT, ST decreased R by 2.5-fold, E by 3.5-fold, and C by 7-fold. Maximum runoff values for Iv events were 1.6-fold higher than those for Ic events and occurred 38 min earlier. Values for Etot and Ctot for Iv events were 19-36% and 1.5-fold higher than corresponding values for Ic events. Values for Emax and Cmax for Iv events were 3-fold and 4-fold higher than corresponding values for Ic events. Carbon enrichment ratios (CER) were or=1.0 for CT plots (except for first 20 min). Maximum CER for CT-Ic, CT-Iv, ST-Ic, and ST-Iv were 2.0, 2.2, 1.0, and 1.2, respectively. Transport of sediment, carbon, and agrichemicals would be better understood if variable rainfall intensity patterns derived from natural rainfall were used in rainfall simulations to evaluate their fate and transport from CT and ST systems.     

STORM CHARACTERISTICS OF CONVECTIVE-SCALE PRECIPITATION1

A classification scheme for convective precipitation, having applications in both analysis and modeling of meteorological and hydrological events, is presented. The method is based upon observations of rainfall at the ground, radar scans of storm events, and visible and infrared satellite imagery of larger storm systems. Empirical and theoretical frequency distributions are derived for total storm rainfall, rainfall duration and time between storms for each of the convective categories. This stratification is directly applicable to the experimental design and evaluation of weather modification projects and may be useful for the development and interpretation of meteorological and hydrological models. When atmospheric conditions limit storm development to cells, rainfall was seldom observed. Small clusters also produce small amounts of rainfall but have a longer lifetime than cells and are likely candidates for cloud seeding attempts to encourage their growth to large clusters. Large and nested clusters usually produce large amounts of natural precipitation. A few large storms account for most of a season's rainfall.     

Satellite Rainfall Estimates Over South America – Possible Applicability to the Water Management of Large Watersheds1

Pereira Filho, Augusto J., Richard E. Carbone, John E. Janowiak, Phillip Arkin, Robert Joyce, Ricardo Hallak, and Camila G.M. Ramos, 2010. Satellite Rainfall Estimates Over South America – Possible Applicability to the Water Management of Large Watersheds. Journal of the American Water Resources Association (JAWRA) 46(2):344-360. DOI: 10.1111/j.1752-1688.2009.00406.x Abstract: This work analyzes high-resolution precipitation data from satellite-derived rainfall estimates over South America, especially over the Amazon Basin. The goal is to examine whether satellite-derived precipitation estimates can be used in hydrology and in the management of larger watersheds of South America. High spatial-temporal resolution precipitation estimates obtained with the CMORPH method serve this purpose while providing an additional hydrometeorological perspective on the convective regime over South America and its predictability. CMORPH rainfall estimates at 8-km spatial resolution for 2003 and 2004 were compared with available rain gauge measurements at daily, monthly, and yearly accumulation time scales. The results show the correlation between satellite-derived and gauge-measured precipitation increases with accumulation period from daily to monthly, especially during the rainy season. Time-longitude diagrams of CMORPH hourly rainfall show the genesis, strength, longevity, and phase speed of convective systems. Hourly rainfall analyses indicate that convection over the Amazon region is often more organized than previously thought, thus inferring that basin scale predictions of rainfall for hydrological and water management purposes have the potential to become more skillful. Flow estimates based on CMORPH and the rain gauge network are compared to long-term observed average flow. The results suggest this satellite-based rainfall estimation technique has considerable utility. Other statistics for monthly accumulations also suggest CMORPH can be an important source of rainfall information at smaller spatial scales where in situ observations are lacking.     

RELATIONSHIPS BETWEEN LAND USES AND RAINWATER QUALITY IN A SOUTHCENTRAL PENNSYLVANIA WATERSHED1

ABSTRACT: Spatial and temporal variability in rainfall concentrations of nutrients, major ions, and herbicides was monitored at 7 locations in or near the Conodoguinet Creek watershed in south-central Pennsylvania from 1991.1993. Results were used to (1) compare precipitation quality in forested, agricultural and urban areas, and (2) assess the practicality of using volunteer citizen monitoring in such a study. As indicated in previous studies, sulfate and nitrogen concentrations in precipitation were linked to sample pH. Concentrations of major ions in precipitation appeared to relate more to regional influences rather than local influences. However, concentrations of herbicides in precipitation may have been influenced by both regional and local use which caused compounds like atrazine, deethylatrazine, propazine, simazine, metolachior, alachlor, ametryn, and prometon to be present in detectable concentrations in rainfall. Seasonality was evident in nitrogen, sulfate, pH, and herbicide data and was suggested in calcium, iron, manganese, magnesium, orthophosphate, and chloride data. Agricultural weed control activities were probably responsible for the seasonal pattern in pesticide data which peaked in May and June. Tropical storm Danielle may have caused the apparent seasonal patterns for the other nine parameters. This storm did not follow the typical west to east movement pattern and consequently produced rainfall of relative high quality. A variety of quality assurance checks indicated that trained volunteer citizen monitors were successful participants in this intensive and extensive scientific study, collecting good quality samples in a timely manner. Without this kind of volunteer help, it is extremely difficult to complete studies that require sampling in response to natural events such as rainfall.     

Climate and Land Use Effects on Hydrologic Processes in a Primarily Rain‐Fed,Agricultural Watershed

Anticipating changes in hydrologic variables is essential for making socioeconomic water resource decisions. This study aims to assess the potential impact of land use and climate change on the hydrologic processes of a primarily rain‐fed, agriculturally based watershed in Missouri. A detailed evaluation was performed using the Soil and Water Assessment Tool for the near future (2020–2039) and mid‐century (2040–2059). Land use scenarios were mapped using the Conversion of Land Use and its Effects model. Ensemble results, based on 19 climate models, indicated a temperature increase of about 1.0°C in near future and 2.0°C in mid‐century. Combined climate and land use change scenarios showed distinct annual and seasonal hydrologic variations. Annual precipitation was projected to increase from 6% to 7%, which resulted in 14% more spring days with soil water content equal to or exceeding field capacity in mid‐century. However, summer precipitation was projected to decrease, a critical factor for crop growth. Higher temperatures led to increased potential evapotranspiration during the growing season. Combined with changes in precipitation patterns, this resulted in an increased need for irrigation by 38 mm representing a 10% increase in total irrigation water use. Analysis from multiple land use scenarios indicated converting agriculture to forest land can potentially mitigate the effects of climate change on streamflow, thus ensuring future water availability.