Refine
Document Type
- Article (3)
- Doctoral Thesis (1)
Language
- English (4)
Is part of the Bibliography
- yes (4)
Keywords
- Carbic Podzol (1)
- Fernerkundungsprodukte (1)
- Final run (1)
- Global precipitation measurement (1)
- Gridded rainfall (1)
- Grundwasserneubildung (1)
- Haplic Acrisol (1)
- Hyetograph classification (1)
- MIT (1)
- MRD (1)
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-December 2016 (daily, monthly, and annual basis). The analysis consisted of comparing the satellite-based estimates against a ground-based gridded rainfall product created using daily records from 4911 rain gauges distributed throughout Brazil. Overall, the results show that the IMERG product can effectively capture the spatial patterns of rainfall across Brazil. However, the IMERG product presents a slight tendency in overestimating the ground-based rainfall at all timescales. Furthermore, the performance of the satellite product varies throughout the region. The higher errors and biases are found in the North and Central-West regions, but the low density of rain gauges in those regions can be a source of large deviations between IMERG estimates and observations. A large underestimation of the IMERG data is evident along the coastal zone of the North-east region, probably due to the inability of the passive microwave and infrared sensors to detect warm-rain processes over land. This study shows that the IMERG product can be a good source of rainfall data to complement the ground precipitation measurements in most of Brazil, although some uncertainties are found and need to be further studied
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 Humiluvico 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.
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 (Guaraira, GEB, Sao Joao 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.
Studies on the unsustainable use of groundwater resources are still considered incipient since it is frequently a poorly understood and managed, devalued and inadequately protected natural resource. Groundwater Recharge (GWR) is one of the most challenging elements to estimate since it can rarely be measured directly and cannot easily be derived from existing data. To overcome these limitations, many hydro(geo)logists have combined different approaches to estimate large-scale GWR, namely: remote sensing products, such as IMERG product; Water Budget Equation, also in combination with hydrological models, and; Geographic Information System (GIS), using estimation formulas. For intermediary-scale GWR estimation, there exist: Non-invasive Cosmic-Ray Neutron Sensing (CRNS); wireless networks from local soil probes; and soil hydrological models, such as HYDRUS. Accordingly, this PhD thesis aims, on the one hand, to demonstrate a GIS-based model coupling for estimating the GWR distribution on a large scale in tropical wet basins. On the other hand, it aims to use the time series from CRNS and invasive soil moisture probes to inversely calibrate the soil hydraulic properties, and based on this, estimating the intermediary-scale GWR using a soil hydrological model. For such purpose, two tropical wet basins located in a complex sedimentary aquifer in the coastal Northeast region of Brazil were selected. These are the João Pessoa Case Study Area and the Guaraíra Experimental Basin. Several satellite products in the first area were used as input to the GIS-based water budget equation model for estimating the water balance components and GWR in 2016 and 2017. In addition, the point-scale measurement and CRNS data were used in the second area to determine the soil hydraulic properties, and to estimate the GWR in the 2017-2018 and 2018-2019 hydrological years. The resulting values of GWR on large- and intermediary-scale were then compared and validated by the estimates obtained by groundwater table fluctuations. The GWR rates for IMERG- and rain-gauge-based scenarios showed similar coefficients between 68% and 89%, similar mean errors between 30% and 34%, and slightly-different bias between -13% and 11%. The results of GWR rates for soil probes and CRNS soil moisture scenarios ranged from -5.87 to -61.81 cm yr-1, which corresponds to 5% and 38% of the precipitation. The calculations of the mean GWR rates on large-scale, based on remote sensing data, and on intermediary-scale, based on CRNS data, held similar results for the Podzol soil type, namely 17.87% and 17% of the precipitation. It is then concluded that the proposed methodologies allowed for estimating realistically the GWR over the study areas, which can be a ground-breaking step towards improving the water management and decision-making in the Northeast of Brazil.