Rainfall data from the Global Precipitation Measurement (GPM) mission provide a new source of information with high spatiotemporal resolution that overcomes the limitations of ground-based rainfall information worldwide. This study evaluates the performance of the Integrated Multi-satellitE Retrievals for GPM (IMERG) Final Run product over Brazil by means of multi-temporal and -spatial analyses. The assessment of the IMERG Final Run product is based on six statistics obtained for the period between January-

Sub-daily rainfall information is essential for many hydrological applications, but groundbased data availability is still an issue in poorly gauged regions worldwide. Satellite remote sensing missions, such as the Global Precipitation Measurement (GPM) mission, have been playing a key role in estimating sub-daily rainfall data globally. However, the quality of such information needs to be carefully evaluated.Previous studies evaluating sub-daily data from the Integrated multi-satellitE Retrievals for GPM (IMERG) product considered only the rainfall depth over pre-defined periods (e.g., hourly or half-hourly), with no analysis of the ability and quality of the product in defining the actual rainfall events and the associated properties. Thus, the objective of this study is to evaluate the performance of the IMERG Final Run Version *Revised Manuscript with no changes marked Click here to view linked References

This paper aims to evaluate the characteristics of rainfall events of three experimental basins located in northeast Brazil. The study areas are located, one in Ceará State and two in Paraíba State. Thus, the definition of rainfall events was based on two characteristics: minimum inter-event time and minimum event depth. Then, they were classified according to the shape of the hyetograph: to the left rectangular, triangular, and triangular with peak, and to the right, bimodal and unshaped. Evaluation of the percentages of each type of hyetograph and the main characteristics of rainfall events (peak, duration and intensity) was carried out. The results shows that the two experimental basins located in the semi-arid region have similar characteristics, and shapeless events have significant accumulated rainfall.

The lack of process-based classification procedures may lead to unrealistic hyetograph design due to complex oscillation of rainfall depths when assimilated at high temporal resolutions. Four consecutive years of sub-hourly rainfall data were assimilated in three study areas (Guaraíra, GEB, São João do Cariri, CEB, and Aiuaba, AEB) under distinct climates (very hot semi-arid and tropical wet). This study aimed to define rainfall events (for Minimum Inter-event Time, MIT, and Minimum Rainfall Depth, MRD, equal to 30 min and 1.016 mm, respectively), classify their hyetograph types (rectangular, R, unimodal with left-skewed, UL, right-skewed, UR, and centred peaks, UC, bimodal, B, and shapeless, SL), and compare their key rainfall properties (frequency, duration, depth, rate and peak). A rain pulse aggregation process allowed for reshaping SL-events for six different time spans varying from 2 to 30 min. The results revealed that the coastal area held predominantly R-events (64% events and 49% rainfall depth), in western semi-arid prevailed UL-events (57% events and 63% rainfall depth), whereas in eastern semi-arid mostly were R-events (61% events and 30% rainfall depth) similar to coastal area. It is concluded that each cloud formation type had important effects on hyetograph properties, differentiating them even within the same climate.

Above and underground hydrological processes depend on soil moisture (SM) variability, driven by different environmental factors that seldom are well-monitored, leading to a misunderstanding of soil water temporal patterns. This study investigated the stability of the SM temporal dynamics to different monitoring temporal resolutions around the border between two soil types in a tropical watershed. Four locations were instrumented in a small-scale watershed (5.84 km 2) within the tropical coast of Northeast Brazil, encompassing different soil types (Espodossolo Humilúvico or Carbic Podzol, and Argissolo Vermelho-Amarelo or Haplic Acrisol), land covers (Atlantic Forest, bush vegetation, and grassland) and topographies (flat and moderate slope). The SM was monitored at a temporal resolution of one hour along the 2013-2014 hydrological year and then resampled a resolutions of 6 h, 12 h, 1 day, 2 days, 4 days, 7 days, and 15 days. Descriptive statistics, temporal variability, time-stability ranking, and hierarchical clustering revealed uneven associations among SM time components. The results show that the time-invariant component ruled SM temporal variability over the time-varying parcel, either at high or low temporal resolutions. Time-steps longer than 2 days affected the mean statistical metrics of the SM time-variant parcel. Additionally, SM at downstream and upstream sites behaved differently, suggesting that the temporal mean was regulated by steady soil properties (slope, restrictive layer, and soil texture), whereas their temporal anomalies were driven by climate (rainfall) and hydrogeological (groundwater level) factors. Therefore, it is concluded that around the border between tropical soil types, the distinct behaviour of time-variant and time-invariant components of SM time series reflects different combinations of their soil properties.

No abstract

Although cosmic-ray neutron sensing (CRNS) is probably the most promising noninvasive proximal soil moisture measurement technique at the field scale, its application for hydrological simulations remains underexplored in the literature so far. This study assessed the use of CRNS to inversely calibrate soil hydraulic parameters at the intermediate field scale to simulate the groundwater recharge rates at a daily timescale. The study was conducted for two contrasting hydrological years at the Guaraíra experimental basin, Brazil, a 5.84-kmš, a tropical wet and rather flat landscape covered by secondary Atlantic forest. As a consequence of the low altitude and proximity to the equator low neutron count rates could be expected, reducing the precision of CRNS while constituting unexplored and challenging conditions for CRNS applications. Inverse calibration for groundwater recharge rates was used based on CRNS or pointscale soil moisture data. The CRNS-derived retention curve and saturated hydraulic conductivity were consistent with the literature and locally performed slug tests. Simulated groundwater recharge rates ranged from 60 to 470 mm yr -1 , corresponding to 5 and 29% of rainfall, and correlated well with estimates based on water table fluctuations. In contrast, the estimated results based on inversive point-scale datasets were not in alignment with measured water table fluctuations. The better performance of CRNS-based estimations of field-scale hydrological variables, especially groundwater recharge, demonstrated its clear advantages over traditional invasive point-scale techniques. Finally, the study proved the ability of CRNS as practicable in low altitude, tropical wet areas, thus encouraging its adoption for water resources monitoring and management.

ABSTRACT:In 2003, a network for hydrology of the semiarid region (REHISA in Portuguese) was created in Brazil. Since then, experimental watersheds in this region has been providing hydrometeorological data collected in automatic stations. However, the spatial distribution of these gauges might be insufficient to thoroughly understand the hydrological processes occurring in the area. Remotely sensed hydrological variables presents a possible way to overcome such limitations as long as these estimates prove to have enough accuracy. This paper compares the monitored yearly and monthly rainfall in the Guaraíra experimental watershed with data from the Tropical Rainfall Measuring Mission (TRMM) 3B42 Version-7 product. The study area has a drainage area of 5.84 km² and is located in the coastal region of Paraíba State, where the mean annual rainfall is 1,700 mm. Two automatic stations provided rainfall data from 2004 to 2011 to assess the satellite estimates in annual and monthly basis. TRMM 3B42V7 performance was evaluated based on graphical analysis. In the annual analysis, relative error ranged from 3 to -51%, however due to the monthly variation, such errors seemed to be insufficient to draw any conclusion, regarding the monthly results. For instance, when the relative error was 3% (difference of 48.3 mm for year 2004), the monthly analysis showed that this was due to a compensation occurred during the year, this is, a month for which rainfall was significantly underestimated by TRMM was compensated by another one when the satellite rainfall was overestimated. On the opposite, in 2007 (relative error 51%, 855 mm of difference), the monthly data analysis showed that just 4 months presented observed data overestimation, but it was enough to result in such annual overestimation. The monthly analysis showed that 29% of the months presented difference between observed rainfall and TRMM data greater than 70 mm and less than 386 mm, which can be considered a relevant error. 72.4% of these cases (monthly analyses) occurred in years in which the annual rainfall were within the ordinary mean (from 1,205 to 1,760 mm/year). Another important result is the underestimation cases were concentrated on the second part of the rainy period. Thus, conclusions points out that TRMM estimates can provide useful information on annual basis, but users should be aware concerning the underestimation, specially on monthly basis for the studied region. *Corresponding author. This is useful to know for communication with the appropriate person in cases with more than one author.