Assessment of the TRMM 3B42 Precipitation Product in Southern Brazil

The increase in the use of satellite‐derived precipitation products generated by different methods and algorithms emphasizes the need for a deeper analysis of their quality and accuracy. Using the contingency table method, we evaluated the accuracy of versions 6 and 7 of the Tropical Rainfall Measuring Mission Precipitation (TRMM) 3B42 product in southern Brazil by comparing daily precipitation over 13 years (V6 was tested for historical context). The interpolated data from 25 rain gauges were compared with both versions of TRMM. The V7 product tended to produce a slight increase in PC (proportion correct). V7 also showed a slight increase in the correlation coefficient (CC) and a significant increase in the H (hit rate) and CSI (critical success) indexes. However, the upgraded version shows an undesirable increase in the false alarm ratio. When the rainfall volumes were compared, V6 clearly underestimated the total rainfall over the entire period, but the V7 product slightly overestimated the cumulative volume (11%) which still represented a more reliable estimate than from V6. Furthermore, the main improvement in V7 was a large increase in the quantitative recognition of extreme precipitation events: V6 detected only 1% of the daily rainfalls above 60 mm, whereas V7 detected 57% of the events.     

FOG DRIP IN THE BULL RUN MUNICIPAL WATERSHED,OREGON1

ABSTRACT: Net precipitation under old growth Douglas fir forest in the Bull Run Municipal Watershed (Portland, Oregon) totaled 1739 mm during a 4Cbweek period, 387 mm more than in adjacent clearcut areas. Expressing data on a full water year basis and adjusting gross precipitation for losses due to rainfall interception suggest fog drip could have added 882 mm (35 in) of water to total precipitation during a year when precipitation measured 2160 mm in a rain gage in a nearby clearing. Standard rain gages installed in open areas where fog is common may be collecting up to 30 percent less precipitation than would be collected in the forest. Long term forest management (Le., timber harvest) in the watershed could reduce annual water yield and, more importantly, summer stream flow by reducing fog drip.     

Role of Riparian Areas in Atmospheric Pesticide Deposition and Its Potential Effect on Water Quality

Riparian buffers are known to mitigate hydrologic losses of nutrients and other contaminants as they exit agricultural fields. The vegetation of riparian buffers can also trap atmospheric contaminants, and these pollutants can subsequently be delivered via rain to the riparian buffer floor. These processes, however, are poorly understood especially for pesticide residues. Therefore, we conducted a four‐year study examining stemflow and throughfall to a riparian buffer which was adjacent a cultured Zea mays field treated with atrazine and metolachlor. Stemflow is rain contacting the tree canopy traveling down smaller to larger branches and down the tree trunk, whereas throughfall is rain that may or may not contact leaves and branches and reaches the earth. Stemflow concentrations of the herbicides were larger than throughfall concentrations and accounted for 5‐15% of the atrazine and 6‐66% of the metolachlor depositional fluxes under the canopy. Larger depositional fluxes were measured when leaves were more fully emerged and temperatures and humidity were elevated. Rain collected outside the riparian buffer on the field side and on the back side revealed the trees trapped the herbicide residues. Herbicide loading to the riparian buffer stream was found to be linked to tree canopy deposition and subsequent washoff during rain events. These results indicate that in agricultural areas canopy washoff can be an important source of pesticides to surface waters.     

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.     

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.     

Neural Network Input Selection for Hydrological Forecasting Affected by Snowmelt1

Abstract: Snowmelt largely affects runoff in watersheds in Nordic countries. Neural networks (NN) are particularly attractive for streamflow forecasting whereas they rely at least on daily streamflow and precipitation observations. The selection of pertinent model inputs is a major concern in NNs implementation. This study investigates performance of auxiliary NN inputs that allow short‐term streamflow forecasting without resorting to a deterministic snowmelt routine. A case study is presented for the Rivière des Anglais watershed (700 km²) located in Southern Québec, Canada. Streamflow (Q), precipitations (rain R and snow S, or total P), temperature (T) and snow lying (A) observations, combined with climatic and snowmelt proxy data, including snowmelt flow (Q_SM) obtained from a deterministic model, were tested. NN implemented with antecedent Q and R produced the largest gains in performance. Introducing increments of A and T to the NNs further improved the performance. Long‐term averages, seasonal data, and Q_SM failed to improve the networks.     

Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part II: An Application of Metrics and Adjoints

We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

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.     

Thermal Characteristics of Stormwater Runoff from Asphalt and Sod Surfaces1

Abstract: Urban impervious surfaces absorb and store thermal energy, particularly during warm summer months. During a rainfall/runoff event, thermal energy is transferred from the impervious surface to the runoff, causing it to become warmer. As this higher temperature runoff enters receiving waters, it can be harmful to coldwater habitat. In an urban watershed, impervious asphalt surfaces (roads, parking lots, and driveways) and pervious residential lawns comprise a significant portion of the watershed area. A paired asphalt‐turfgrass sod plot was constructed to compare the thermal runoff characteristics between asphalt and turfgrass sod surfaces, to identify meteorological variables that influence these thermal characteristics, and to evaluate evaporative heat loss for runoff from asphalt surfaces. Rainfall simulations were conducted during the summers of 2004 and 2005 under a range of climatic conditions. Asphalt surface temperatures immediately prior to rainfall simulations averaged 43.6°C and decreased an average of 12.3°C over 60 min as rain cooled the surface. In contrast, presimulation sod surface temperatures averaged only 23.3°C and increased an average of 1.3°C throughout the rainfall events. Heat transferred from the asphalt to the runoff resulted in initial asphalt runoff temperatures averaging 35.0°C that decreased by an average of 4.1°C at the end of the event. Sod runoff temperatures averaged only 25.5°C and remained fairly constant throughout the simulations. Multivariable regression equations were developed to predict (1) average asphalt surface temperature (R² = 0.90) and average asphalt runoff temperature (R² = 0.92) as a function of solar radiation, rain temperature, and wind speed, and (2) average sod surface temperature (R² = 0.85) and average sod runoff temperature (R² = 0.94) as a function of solar radiation, rain temperature, rain intensity, and wind speed. Based on a heat balance analysis, existing evaporation equations developed from studies on lakes were not adequate to predict evaporation from runoff on a heated impervious surface. The combined heat from the asphalt and sod plots was an average of 38% less than the total heat had the total area consisted solely of asphalt.     

Trends in Rainfall Exceedances in the Observed Record in Selected Areas of the United States1

Bonnin, Geoffrey M., Kazungu Maitaria, and Michael Yekta, 2011. Trends in Rainfall Exceedances in the Observed Record in Selected Areas of the United States. Journal of the American Water Resources Association (JAWRA) 47(6): 1173–1182. DOI: 10.1111/j.1752‐1688.2011.00603.x Abstract: Semantic differences have led to a gap in the understanding of the impacts of climate change on precipitation frequency estimates. There is popular perception that heavy rainfalls have become more frequent, and that this trend will increase with global warming. Most of the literature examines this question from the point of view of climatology using definitions of “heavy,”“very heavy,” or “extreme” rainfall, which are different from those commonly used by civil engineers. This article identifies the differences in meaning used by the climate and civil engineering communities and examines trends in the observed record in the frequency of exceedances (not trends in magnitudes). Using concepts recognized as the basis for design of the Nation’s civil infrastructure, we look at trends in the number of exceedances of thresholds for a variety of precipitation frequencies and event durations used by civil engineers. We found that the estimated trends in exceedances at one‐day and multiday durations were statistically significant and increasing for the Ohio River Basin and surrounding states but the reverse was true for the Semiarid Southwest (i.e., not significant and decreasing trends). In addition, we found the magnitude of the trends was small for all but the more frequent events and also small with respect to the uncertainty associated with the precipitation frequency estimates themselves.     

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.     

Rainfall Runoff Relationships for a Cloud Forest Watershed in Central America: Implications for Water Resource Engineering1

Caballero, Luis A., Alon Rimmer, Zachary M. Easton, and Tammo S. Steenhuis, 2012. Rainfall Runoff Relationships for a Cloud Forest Watershed in Central America: Implications for Water Resource Engineering. Journal of the American Water Resources Association (JAWRA) 48(5): 1022‐1031. DOI: 10.1111/j.1752‐1688.2012.00668.x Abstract: Understanding the basic relationships between rainfall and runoff is vital for effective management and utilization of scarce water resources. Especially, this is important in Central America with widespread potable water shortage during the dry months of the monsoon. Potential good water sources are cloud forests, but little information concerning its potential is available to water supply engineers. Our objective is to define rainfall‐runoff‐base flow relationships for a cloud forest catchment. Flumes were installed for measuring river flow in four subwatersheds in La Tigra National Park, Honduras. One of the four watersheds was a 636‐ha subwatershed (WS1) with 60% cloud forest coverage. Precipitation averaged 1,130 mm/yr over the entire basin. About half of the total rainfall became runoff for the cloud forest watershed whereas, for the adjacent undisturbed forested watershed, the total discharge was <20% of the amount of precipitation. Infiltration rates were generally greater than rainfall rates. Therefore, most rainfall infiltrated into the soil, especially in the upper, steep, and well‐drained portions of the watershed. Direct runoff was generated from saturated areas near the river and exposed bedrock. This research provides compelling evidence that base flow is the primary contributor to streamflow during both wet and dry seasons in cloud forest catchments. Protecting these flow processes over time is critical for the sustained provision of potable water.     

400 YEARS OF CENTRAL CALIFORNIA PRECIPITATION VARIABILITY RECONSTRUCTED FROM TREE-RINGS1

ABSTRACT: Coastal central California is a region that has never been the subject of tree-ring studies. New tree-ring chronologies developed from cores of big cone spruce (Pseudotusuga macrocarpa (Torr.) Mayr.) growing in the Transverse Ranges of central Santa Barbara county were used to reconstruct precipitation fluctuations for this region. To verify the new reconstructions, calibration with recorded rainfall using cross-validation, comparison with other reconstructions, and documentary evidence from historical sources were utilized. The precipitation reconstructions show that there have not been fluctuations in mean precipitation on time scales longer than 30 years, but there have been major fluctuations in precipitation variability including changes in the frequency of extremes and rare events that have not occurred in the modern record.     

Responses of Soil CO<Subscript>2</Subscript> Efflux to Precipitation Pulses in Two Subtropical Forests in Southern China

This study was designed to examine the responses of soil CO₂ efflux to precipitation pulses of varying intensities using precipitation simulations in two subtropical forests [i.e., mixed and broadleaf forests (MF and BF)] in southern China. The artificial precipitation event was achieved by spraying a known amount of water evenly in a plot (50 × 50 cm²) over a 30 min period, with intensities ranging from 10, 20, 50 and 100 mm within the 30 min. The various intensities were simulated in both dry season (in December 2007) and wet (in May 2008) season. We characterized the dynamic patterns of soil CO₂ efflux rate and environmental factors over the 5 h experimental period. Results showed that both soil moisture and soil CO₂ efflux rate increased to peak values for most of the simulated precipitation treatments, and gradually returned to the pre-irrigation levels after irrigation in two forests. The maximum peak of soil CO₂ efflux rate occurred at the 10 mm precipitation event in the dry season in BF and was about 3.5 times that of the pre-irrigation value. The change in cumulative soil CO₂ efflux following precipitation pulses ranged from −0.68 to 1.72 g CO₂ m⁻² over 5 h compared to the pre-irrigation levels and was generally larger in the dry season than in the wet season. The positive responses of soil CO₂ efflux to precipitation pulses declined with the increases in precipitation intensity, and surprisingly turned to negative when precipitation intensity reached 50 and 100 mm in the wet season. These findings indicated that soil CO₂ efflux could be changed via pulse-like fluxes in subtropical forests in southern China as fewer but extreme precipitation events occur in the future.     

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.     

APPLICATION OF THE GREEN-AMPT INFILTRATION EQUATION TO WATERSHED MODELING1

ABSTRACT: A computer model was developed, based on the Green-Ampt infiltration equation, to computed rainfall excess for a single precipitation event. The model requires an estimate of parameters related to hydraulic conductivity, wetting front section, and fillable porosity of the soil layers. Values of parameters were estimated from soil textural averages or regression equations based on percent sand, percent clay, and porosity. Average values of effective porosity and wetting front suction were largely acceptable due to the relatively low variability and low model sensitivity to the parameters. Hydraulic conductivity was the most erratic constituent of the loss rate computation due to the high variability and the high sensitivity of the computed infiltration to the parameter. The performance of the Green-Ampt infiltration model was tested through a comparison with the SCS curve number procedure. Seven watersheds and 23 storms with precipitation of one inch or greater were used in the comparison. For storms with less than one inch of rainfall excess, the SCS curve number procedure generally gave the best results; however, for six of the seven storms with precipitation excess greater than one inch, the Green-Ampt procedure delivered better results. In this comparison, both procedures used the same initial abstractions. The separation of rainfall losses into infiltration, interception, and surface retention is, in theory, an accurate method of estimating precipitation excess. In the second phase of the study using nine watersheds and 39 storms, interception and surface retention losses were computed by the Horton equations. Green-Ampt and interception parameters were estimated from value sin the literature, while the surface retention parameter was calibrated so that the computed runoff volumes matched observed volumes. A relationship was found between the surface retention storage capacity and the 15-day antecedent precipitation index, month of year, and precipitation amount.     

Effect of Rainfall Regime and Slope on Runoff in a Gullied Loess Region on the Loess Plateau in China

Runoff was measured from seven plots with different slopes nested in Tuanshangou catchment on the Loess Plateau to study effect of slopes on runoff in relation to rainfall regimes. Based on nine years of field observation and K-mean clusters, 84 rainfall events were grouped into three rainfall regimes. Rainfall regime A is the group of events with strong rainfall intensity, high frequency, and short duration. Rainfall regime C consists of events with low intensity, long duration, and infrequent occurrence. Rainfall regime B is the aggregation of events of medium intensity and medium duration, and less frequent occurrence. The following results were found: (1) Different from traditional studies, runoff coefficient neither decreased nor increased, but presented peak value on the slope surfaces; (2) For individual plot, runoff coefficients induced by rainfall regime A were the highest, and those induced by rainfall regime C were the lowest; Downslope, the runoff coefficients induced by three rainfall regimes presented the same changing trend, although the peak value induced by regime A occurred on a shorter slope length compared to those by regime B and C; (3) Scale effect on runoff induced by rainfall regime A was the least, and that induced by rainfall regime C was the largest. These results can be explained by the interactions of crusting, soil moisture content, slope length and gradient, and erosion units, etc., in the context of different rainfall regimes.     

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.