Multi-scale investigation on streamflow temporal variability and its connection to global climate indices for unregulated rivers in India

With the increasing stress on water resources for a developing country like India, it is pertinent to understand the dominant streamflow patterns for effective planning and management activities. This study investigates the spatiotemporal characterization of streamflow of six unregulated catchments in India. Firstly, Mann Kendall (MK) and Changepoint analysis were carried out to detect the presence of trends and any abrupt changes in hydroclimatic variables in the chosen streamflows. To unravel the relationships between the temporal variability of streamflow and its association with precipitation and global climate indices, namely, Niño 3.4, IOD, PDO, and NAO, continuous wavelet transform is used. Cross-wavelet transform and wavelet coherence analysis was also used to capture the coherent and phase relationships between streamflow and climate indices. The continuous wavelet transforms of streamflow data revealed that intra-annual (0.5 years), annual (1 year), and inter-annual (2–4 year) oscillations are statistically significant. Furthermore, a better understanding of the in-phase relationship between the streamflow and precipitation at intra-annual and annual time scales were well-captured using wavelet coherence analysis compared to cross wavelet transform. Furthermore, our analysis also revealed that streamflow observed an in-phase relationship with IOD and NAO, whereas a lag correlation with Niño 3.4 and PDO indices at intra-annual, annual and interannual time scales.

Climate and Land Cover Trends Affecting Freshwater Inputs to a Fjord in Northwestern Patagonia

Freshwater inputs strongly influence oceanographic conditions in coastal systems of northwestern Patagonia (41–45°S). Nevertheless, the influence of freshwater on these systems has weakened in recent decades due to a marked decrease in precipitation. Here we evaluate potential influences of climate and land cover trends on the Puelo River (640 m3s–1), the main source of freshwater input of the Reloncaví Fjord (41.5°S). Water quality was analyzed along the Puelo River basin (six sampling points) and at the discharge site in the Reloncaví Fjord (1, 8, and 25 m depth), through six field campaigns carried out under contrasting streamflow scenarios. We also used several indicators of hydrological alteration, and cross-wavelet transform and coherence analyses to evaluate the association between the Puelo River streamflow and precipitation (1950–2019). Lastly, using the WEAP hydrological model, land cover maps (2001–2016) and burned area reconstructions (1985–2019), we simulated future land cover impacts (2030) on the hydrological processes of the Puelo River. Total Nitrogen and total phosphorus, dissolved carbon, and dissolved iron concentrations measured in the river were 3–15 times lower than those in the fjord. Multivariate analyses showed that streamflow drives the carbon composition in the river. High streamflow conditions contribute with humic and colored materials, while low streamflow conditions corresponded to higher arrival of protein-like materials from the basin. The Puelo River streamflow showed significant trends in magnitude (lower streamflow in summer and autumn), duration (minimum annual streamflow), timing (more floods in spring), and frequency (fewer prolonged floods). The land cover change (LCC) analysis indicated that more than 90% of the basin area maintained its land cover, and that the main changes were attributed to recent large wildfires. Considering these land cover trends, the hydrological simulations project a slight increase in the Puelo River streamflow mainly due to a decrease in evapotranspiration. According to previous simulations, these projections present a direction opposite to the trends forced by climate change. The combined effect of reduction in freshwater input to fiords and potential decline in water quality highlights the need for more robust data and robust analysis of the influence of climate and LCC on this river-fjord complex of northwestern Patagonia.

Effects of Climate Change on Cultivation Patterns and Climate Suitability of Spring Maize in Inner Mongolia

Climate change has caused significant alterations in crop cultivation patterns and has affected crop suitability as well as its production. In this study, we investigated the changes in cultivation patterns and climate suitability of spring maize in Inner Mongolia from 1959 to 2018. We used the daily meteorological data from 50 weather stations and growth period data of spring maize from nine agrometeorological stations. In addition, the quantitative and interdecadal relationship between climate suitability of regions and climate-induced crop yield was analyzed using stepwise regression and cross wavelet transform. The results show that: (1) The planting boundaries of different spring maize maturity types extend to the north and east. In the middle part, early maturity maize has been replaced by medium maturity maize. The unsuitable planting areas in Northeast Inner Mongolia are decreasing, and the early maturity areas are increasing. (2) The climate suitability for spring maize planting areas is increasing. However, variations occur between different regions; the eastern region has the highest climate suitability (Sz = 0.67), but the overall trend is decreasing in this region. Whereas the central region has moderate suitability (Sz = 0.62), with a significantly increasing trend (p < 0.05). The western region is lower (Sz = 0.60) and the trend is not significant. (3) Climate suitability and climate-induced yields are generally positively correlated. The primary factors affecting climate-induced yields are sunshine hours, followed by climate suitability, rainfall, and temperature. The cross-wavelet transform shows that climate suitability and climate-induced yield have greater periodicity in the late growth period. Appropriate expansion of the planting range of medium-late maturity spring maize can fully adapt to the impact of climate warming. Therefore, it is necessary to study suitability trends of regions to adopt comprehensive maize production measures.

Estudos de Variabilidades Interanuais e Interdecenais da Precipitação Pluvial das Regiões Hidrográficas Tocantins-Araguaia e São Francisco no Brasil

O objetivo é investigar as fases temporais das variabilidades de precipitação pluvial das Regiões Hidrográficas do Tocantins-Araguaia e São Francisco, como, também, correlacioná-las com índices de anomalias de Temperatura da Superfície do Mar (TSM) do Pacífico, na região do Niño 3.4, utilizando a análise de transformada ondaleta. A área geográfica está localizada entre os paralelos 0,5º S a 20º S e meridianos 34,8º W a 55,4º W. Foram utilizados dados mensais de precipitação observados e de reanálise (1º x 1º), no período de 1945-2016, e de TSM de 1950-2016 provenientes de órgãos governamentais nacionais e internacionais. As Ondaletas Contínuas mostraram que as variabilidades dominantes, de precipitação total anual, nas Regiões Hidrográficas do Tocantins-Araguaia e do São Francisco são nas escalas de três a cinco anos, de 11 a 12 anos e em torno de 22 anos. Para ambas as Regiões essas frequências estão em fases, pela Transformada Ondaleta Cruzada e confirmada pela Ondaleta Coerente. Nas análises de Ondaletas Cruzada e Coerente das precipitações com os índices oceânicos se verificou que houve avanço (135º) na série do Niño 3.4 em relação as das precipitações das Regiões nas escalas de três a cinco anos, mas foram verificadas diferenças de fase nas escalas decenais da precipitação das Regiões com os índices oceânicos. Concluiu-se que as variabilidades da precipitação de ambas as Regiões estão em fase e que os eventos ENOS influenciam nas precipitações das Regiões Hidrográficas do Tocantins-Araguaia e São Francisco. Studies of Interannual and Interdecennial Variabiliteis of Rainfall in the Tocantins-Araguaia and São Francisco Hydrographic Regions in Brazil ABSTRACTThe objective is to investigate the temporal phases of the variability of rainfall in the Hydrographic Regions of Tocantins-Araguaia and São Francisco, as well as to correlate them with anomalies indexes of the Sea Surface Temperature (SST) of the Pacific, in the Niño 3.4 region, using wavelet transform analysis. The geographical area is located between the parallels 0.5º S to 20º S and meridians 34.8º W to 55.4º W. We used monthly data of observed and reanalysis precipitation (1º x 1º), in the period from 1945 to 2016, and from 1950 to 2016 for SST. The data are from national and international government agencies. The continuous wavelet showed that the dominant variability of total annual precipitation, in the Hydrographic Regions of Tocantins-Araguaia and São Francisco, are in the frequencies of three to five years, 11 to 12 years and about 22 years. These frequencies are in phases by the cross wavelet transform and confirmed by the coherent wavelet. In the cross and coherent wavelet analysis of the precipitation with the oceanic indices, there was an advance (135º) in the Niño 3.4 series in relation to the precipitation of the Regions in the frequency of three to five years, but phase differences were observed in the decadal frequencies between the precipitation of the Regions and oceanic indices. We concluded that the variability of precipitation in both regions is in phase and that the ENOS events influence the rainfall in the Hydrographic Regions of Tocantins-Araguaia and São Francisco.Keywords: El Niño, hydrographic catchment, wavelet, climate variability.

Signature Matching For Seismic Signal Identification

Seismic signals can be classified as natural or manmade by matching signature of similar events that have occurred in the past. Waveform matching techniques can be effectively used for discrimination since the events with similar location and focal mechanism have similar waveform irrespective of magnitude. The seismic signals are inherently non-stationary in nature. The analysis of such signals can be best achieved in multiresolution framework by resolving the signal using continuous wavelet transform (CWT) in time-frequency plane. In this paper similarity testing and classification of nuclear explosion and earthquake are exploited with correlation, continuous wavelet transform, cross-wavelet transform and wavelet coherence (WC) of P phase of seismogram. Clustering of seismic signals continuous wavelet spectra is performed using maximum covariance analysis. The proposed classifier has an average classification accuracy of 94%.