Evaluation gridded precipitation datasets in Indonesia

This preliminary study evaluates ten gridded precipitation datasets in Indonesia, namely APHRODITE, CMORPH, CHIRPS, GFD, SA-OBS, TMPA 3B42 v7, PERSIAN-CDR at 0.25°, moreover GSMaP_NRT V06, GPM-IMERG (Early-Run) V06, and MSWEP V2 at 0.1» in the period of 2003 to 2015. The evaluation focuses on time series bias using metrics such as Mean Error, Coefficient of Variation, Relative Change (Variability), and Kolmogorov-Smirnov test (KS-test) at daily, monthly, seasonal, and annual time scales. The statistical relationship between the precipitation datasets with reference observational data use Taylor diagrams for evaluating the relative skill of the precipitation dataset. The study aims to evaluate the uncertainty of the precipitation datasets compared to rain gauge datasets. Time series bias of SA-OBS and MSWEP have the nearest value to zero as the best score. The relative skill of monthly rainfall based on rainfall typical shows that MSWEP outperformed in regions A and B, GPM-IMERG in C region. GPM-IMERG's relative skill is outperformed than other datasets at annual time scale in Region A and B, while TMPA 3B42 in Region C. The application of existing precipitation datasets is essential to cope with the limitation of rain gauge observations. This study implicates the development of precipitation products in the Indonesia region.

A Climatic Perspective on the Impacts of Global Warming on Water Cycle of Cold Mountainous Catchments in the Tibetan Plateau: A Case Study in Yarlung Zangbo River Basin

Global warming has a profound influence on global and regional water cycles, especially in the cold mountainous area. However, detecting and quantifying such changes are still difficult because noise and variability in observed streamflow are relatively larger than the long-term trends. In this study, the impacts of global warming on the catchment water cycles in the Yarlung Zangbo River Basin (YZRB), one of most important catchments in south of the Tibetan Plateau, are quantified using a climatic approach based on the relationship between basin-scale groundwater storage and low flow at the annual time scale. By using a quantile regression method and flow recession analysis, changes in low flow regimes and basin-scale groundwater storage at the Nuxia hydrological station are quantified at the annual time scale during 1961–2000. Results show annual low flows (10th and 25th annual flows) of the YZRB have decreased significantly, while long-term annual precipitation, total streamflow, and high flows are statistically unchanged. Annual lowest seven-day flow shows a significantly downward trend (2.2 m3/s/a, p < 0.05) and its timing has advanced about 12 days (2.8 day/10a, p < 0.1) during the study period. Estimated annual basin-scale groundwater storage also shows a significant decreasing trend at a rate of 0.079 mm/a (p < 0.05) over the study period. Further analysis suggests that evaporation increase, decreased snow-fraction, and increased annual precipitation intensity induced by the rising temperature possibly are the drivers causing a significant decline in catchment low flow regimes and groundwater storage in the study area. This highlights that an increase in temperature has likely already caused significant changes in regional flow regimes in the high and cold mountainous regions, which has alarming consequences in regional ecological protection and sustainable water resources management.

Attribution Analysis of Long-Term Trends of Aridity Index in the Huai River Basin, Eastern China

This paper aims to combinedly investigate the spatiotemporal trends of precipitation (Pre), reference evapotranspiration (ET0), and aridity index (AI) by employing nonparametric methods based on daily datasets from 137 meteorological stations during 1961–2014 in the Huai River Basin (HRB). The dominant factors influencing ET0 and AI trends were also explored using the detrended and differential equation methods. Results show that (1) Pre, ET0, and AI were much larger in summer than in other seasons, and AI had a nonsignificant increasing trend in annual time scale, while Pre and ET0 exhibited decreasing trends, but AI showed a downward trend in spring and autumn (becoming drier) and an upward trend during summer and winter due to increased Pre (becoming wetter); (2) lower AI values were identified in north and higher in south, and lower ET0 was identified in south and higher in north in annual time scale, growing season and spring, while ET0 decreased from west to east in summer and winter, the spatial distribution of Pre was similar to that of AI; (3) for ET0 trends, in general, wind speed at two-meter height (u2) was the dominant factor in spring, autumn, winter, and annual time scale, while in other seasons, solar radiation (Rs) played a dominant role; (4) for AI trends, AI was mostly contributed by Pre in spring, autumn, and winter, the Rs contributed the most to AI trend in growing season and summer, then in annual time scale, u2 was the dominant factor; (5) overall, the contribution of Pre to AI trends was much larger than that of ET0 in spring, autumn, and winter, while AI was mostly contributed by ET0 in annual time scale, growing season and summer. The outcomes of the study may improve our scientific understanding of recent climate change effects on dry–wet variations in the HRB; moreover, this information may be utilized in other climatic regions for comparison analyses.

SPI-Based Spatiotemporal Drought over Sri Lanka

Drought is one of the most significant hazards in Sri Lanka. Status of drought in Sri Lanka was assessed using Standardized Precipitation Index (SPI) at 3, 6, and 12 months’ time scales using monthly rainfall (1970 to 2017) data of 54 weather stations. The frequency of drought events was evaluated using SPI, and trend of SPI was also detected using the Mann–Kendall (MK) test and Sen’s slope estimator. The result based on SPI identified hydrological years 1975-76, 1982-83, 1986-87, 1988-89, 2000-01, 2001-02, 2013-14, and 2016-17 as drought years for 52, 32, 35, 33, 33, 31, 31, and 31% of tested stations (54), respectively, at annual time scale. Comparison of the SPI at different time scales revealed that more drought events (SPI ≤ −1) occurred during Yala season than Maha cropping season. Considering the Thiessen polygon average rainfall, more frequent drought events occurred in the dry zone (57%) than the wet (49%) and intermediate zone (47%) at the annual time scale. SPI trend results showed greater increase in drought (59% of stations) during Yala seasons as compared to the Maha cropping season (15% of stations) in Sri Lanka.

Hydro-Meteorological Trends in the Upper Omo-Ghibe River Basin, Ethiopia

This study aimed to assess trends of hydro-meteorological variables in the Upper Omo-Ghibe river basin, Ethiopia. Data records from eleven rainfall, eight air temperature, and five streamflow stations between 1981 to 2008 were investigated. The trends and change points were evaluated for different periods of time depending on data availability. Mann-Kendall and Pettit tests were used to identify trends and change points at a 5% significance level. The tests were applied to mean annual, monthly and seasonal time scales. Rainfall exhibited statistically decreasing trends at a mean annual time scale, while seasonal rainfall depicted heterogeneous results in both directions. For the majority of the stations, air temperature showed statistically significant increasing trends. The magnitude of change in temperature for mean annual, wet and dry season has increased about 0.48, 0.46, and 0.61 °C per decade for Jimma station. The Pettit test revealed that the late 1980s and 1990s were the change points. There is generally a decreasing trend in streamflow. The decline in annual rainfall and rise in temperature affected the streamflow negatively. Overall, the results indicate that trend sand change point times varied considerably across the stations and catchments. The identified significant trends can help to support planning decisions for water management.

Modelling Nitrification Inhibitor Effects on N₂O Emissions after Fall and Spring-Applied Slurry by Reducing Nitrifier NH₄⁺ Oxidation Rate

Reductions in N2O emissions from nitrification inhibitors (NI) are substantial, but remain uncertain because measurements of N2O emissions are highly variable and discontinuous. Mathematical modelling may offer an opportunity to estimate these reductions if the processes causing variability in N2O emissions can be accurately simulated. In this study, the effect of NI was simulated with a simple, time-dependent algorithm to slow NH4&amp;plus; oxidation in the ecosystem model ecosys. Slower nitrification modelled with NI caused increases in soil NH4&amp;plus; concentrations and reductions in soil NO3− concentrations and in N2O fluxes that were consistent with those measured following fall and spring applications of slurry over two years from 2014 to 2016. The model was then used to estimate direct and indirect effects of NI on seasonal and annual emissions. After spring slurry applications, NI reduced N2O emissions modelled and measured during the drier spring of 2015 (35 % and 45%) less than during the wetter spring of 2016 (53 % and 72 %). After fall slurry applications, NI reduced modelled N2O emissions by 58 % and 56 % during late fall in 2014 and 2015, and by 8 % and 33 % during subsequent spring thaw in 2015 and 2016. Modelled reductions were consistent with those from meta-analyses of other NI studies. Simulated NI activity declined over time, so that reductions in N2O emissions modelled with NI at an annual time scale were relatively smaller than those during emission events. These reductions were accompanied by increases in NH3 emissions and reductions in NO3− losses with NI that caused changes in indirect N2O emissions. With further parameter evaluation, the addition of this algorithm for NI to ecosys may allow emission factors for different NI products to be derived from annual N2O emissions modelled under diverse site, soil, land use and weather.

Comparison of Nine Meteorological Drought Indices Over Middle Euphrates Region During Period from 1988 To 2017

The aim of this research is compare between nine drought indices and evaluate their performance with respect to predict and monitoring drought over Middle Euphrates region during period from 1988 to 2017.These indices are RDI, Normal SPI, Gamma SPI, Log SPI, CZI, MCZI, RAI, PN, and DI.Season and annual time scale were used to calculate all indices at Dewaniya, Hilla, Karbala, Najaf, and Semawa stations. The Pearson correlation coefficient between nine drought indices were analyzed. Annual and seasonal results illustrated that the maximum value of correlation between RDI and the other indices was noted with Gamma SPI and Log SPI at all stations. In annual time scale, the correlation coefficient reached to (0.99) at all stations except Hilla station, where it reached to (0.98), while in seasonal time scale the correlation coefficient reached to (0.98) at all stations. The RDI, Gamma SPI and Log SPI indices have similarity of classes and frequencies for drought. They also have similarity of frequencies for wet but there are minimum differences between wet classes compared to other indices. The RDI, Gamma SPI and Log SPI are good indices to predict and monitoring drought in study area in comparison to other indices which mentioned above.

Optimising fishery characteristics through control of an invasive species: strategies for redfin perch control in Lake Purrumbete, Australia

Invasive fish species can present difficult management problems, particularly when the species has recreational value. One such case is redfin perch in Lake Purrumbete, Australia, which have recreational value but have become invasive in the lake. In this study we evaluated removal strategies for redfin perch in Lake Purrumbete with the aim of improving the quality of the recreational fishery. We evaluated removal scenarios for redfin perch with a population model and conducted a sensitivity analysis to determine the robustness of our general results. The results suggest that removal scenarios that direct exploitation, on an annual time scale, at fish ≤150-mm total length, with high levels of exploitation, will result in the greatest reduction in small undesirable fish and the greatest increase in large desirable fish in the lake. This was consistent across most assumptions about life-history characteristics, density-dependent processes and population dynamics rates, suggesting that this management strategy is robust to most relevant biological uncertainties. Furthermore, exploiting redfin perch on an annual time scale would result in the lowest annual variation in the population because of disruption of the age and size structure. These results can help managers choose strategies to manipulate the fishery of Lake Purrumbete to achieve more desirable characteristics.