Rainfall Erosivity in Peru: A New Gridded Dataset Based on GPMIMERG and Comprehensive Assessment (2000–2020)

In soil erosion estimation models, the variable with the greatest impact is rainfall erosivity (RE), which is the measurement of precipitation energy and its potential capacity to cause erosion, and erosivity density (ED), which relates RE to precipitation. The RE requires high temporal resolution records for its estimation. However, due to the limited observed information and the increasing availability of rainfall estimates based on remote sensing, recent research has shown the usefulness of using observed-corrected satellite data for RE estimation. This study evaluates the performance of a new gridded dataset of RE and ED in Peru (PISCO_reed) by merging data from the IMERG v06 product, through a new calibration approach with hourly records of automatic weather stations, during the period of 2000-2020. By using this method, a correlation of 0.7 was found between the PISCO_reed and RE obtained by the observed data. An average annual RE for Peru of 4831 M Jmmha−1h −1 was estimated with a general increase towards the lowland Amazon regions and high values are found on the north-coast Pacific area of Peru. The spatial identification of the most risk areas of erosion, was carried out through a relationship between the ED and rainfall. Both erosivity data sets will allow us to expand our fundamental understanding and quantify soil erosion with greater precision

Impacts of climate changes on the spatiotemporal distribution of precipitation in the western United States

Precipitation in the Intermountain West is characterized by its great variability in both spatial and temporal distributions. Moreover, the spatiotemporal distribution of the precipitation is changing due to the climate changes. In this dissertation, three studies are conducted to investigate the multi-scale temporal variability of precipitation, the performance of current climate models on this variability, the influence of large-scale ocean oscillations on heavy precipitation, and the impact of human induced global warming on storm properties. The first study is to examine the performance of current climate models on the simulation of the multi-scale temporal variability determined from the observed station precipitation data. The results show that the studied Global Circulation Models/Regional Climate Models (GCMs/RCMs) tend to simulate longer storm duration and lower storm intensity as compared to those from observed records. Most GCMs/RCMs fail to produce the high-intensity summer storms caused by local convective heat transport associated with the summer monsoon. Both inter-annual and decadal bands are present in the GCM/RCM-simulated precipitation time series; however, these do not line up to the patterns of large-scale ocean oscillations such as El Nino/La Nina Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). The results also show that these GCMs/RCMs can capture long-term monthly mean as the examined data is bias-corrected and downscaled, but fail to simulate the multi-scale precipitation variability including flood generating extreme events, which suggests their inadequacy for studies on floods and droughts that are strongly associated with the multi-scale temporal precipitation variability. The second study investigates the integrated effect of large-scale ocean oscillations including ENSO, PDO, Atlantic Multi-decadal Oscillation (AMO), and North Atlantic Oscillation (NAO) on the multi-scale temporal variability and spatial distribution of heavy precipitation expressed as total precipitation when daily precipitation is larger than 95th percentile (R95) in the western United States using Empirical Orthogonal Function (EOF) analysis. The analysis has shown that the leading modes of R95 variability and the connections between local R95 and Sea Surface Temperature (SST) over Western United States are seasonally dependent. The first EOF mode of summer R95 is associated with AMO. The first two EOF modes of winter R95 are related to an integrated effects of ENSO, PDO, and NAO which explain nearly half (49%) of the spatial and temporal variance in R95 in this region. Additionally, the coupled effects of these three oceanic-atmospheric oscillations on winter R95 are evaluated by investigating the ENSO-R95 responses modulated by a combination of different PDO and NAO phases. The results have implications for predicting the seasonal precipitation extremes for next few decades over the western United States, which may be useful to forecasters and water managers. In the third study, the potential changes of storm properties including storm duration, inter-storm period, average storm intensity, and within-storm pattern from 10 North American Regional Climate Change Assessment Program (NARCCAP) RCMs with both historical simulations (1968-2000) and future simulations (2038-2070) are evaluated. Results illustrate that NARCCAP RCMs are consistent with observed precipitation in the seasonal variation of storm duration and inter-storm period. The ability to simulate the seasonal trend of average storm intensity varies among locations. Within-storm patterns from RCMs exhibit greater variability than from observed records. Comparisons between historic and future simulations of storm properties indicate that most regions of United States will experience future precipitation projections with shorter storm duration, longer inter-storm period, larger average storm intensity, and unchanged within-storm patterns. The western United States is undergoing rapidly changing social dynamics, pressure from an expanding population and a greater risk of water shortage and flooding. Gaining better knowledge of how climate changes will impact on the spatiotemporal distribution of precipitation will help us on hydrologic modeling and assessment of uncertainty of water sustainability in this region

IMPACT OF CLIMATE CHANGE ON EXTREME HYDROLOGICAL EVENTS IN THE KENTUCKY RIVER BASIN

Anthropogenic activities including urbanization, rapid industrialization, deforestation and burning of fossil fuels are broadly agreed on as primary causes for ongoing climate change. Scientists agree that climate change over the next century will continue to impact water resources with serious implications including storm surge flooding and a sea level rise projected for North America. To date, the majority of climate change studies conducted across the globe have been for large-sized watersheds; more attention is required to assess the impact of climate change on smaller watersheds, which can help to better frame sustainable water management strategies. In the first of three studies described in this dissertation, trends in annual precipitation and air-temperature across the Commonwealth of Kentucky were evaluated using the non-parametric Mann-Kendall test considering meteorological time series data from 84 weather stations. Results indicated that while annual precipitation and mean annual temperature have been stable for most of Kentucky over the period 1950-2010, there is evidence of increases (averages of 4.1 mm/year increase in annual precipitation and 0.01 °C/year in mean annual temperature) along the borders of the Kentucky. Considered in its totality, available information indicates that climate change will occur – indeed, it is occurring – and while much of the state might not clearly indicate it at present, Kentucky will almost certainly not be exempt from its effects. Spatial analysis of the trend results indicated that eastern part of the state, which is characterized by relatively high elevations, has been experiencing decreasing trends in precipitation. In the second study, trends and variability of seven extreme precipitation indices (total precipitation on wet days, PRCPTOT; maximum length of dry and wet periods, CDD and CWD, respectively; number of days with precipitation depth ≥20 mm, R20mm; maximum five-day precipitation depth, RX5day; simple daily precipitation intensity, SDII; and standardized precipitation index, SPI were analyzed for the Kentucky River Basin for both baseline period of 1986-2015 and the late-century time frame of 2070-2099. For the baseline period, the majority of the indices demonstrated increasing trends; however, statistically significant trends were found for only ~11% of station-index combinations of the 16 weather stations considered. Projected magnitudes for PRCPTOT, CDD, CWD, RX5day and SPI, indices associated with the macroweather regime, demonstrated general consistency with trends previously identified and indicated modest increases in PRCPTOT and CWD, slight decreases in CDD, mixed results for RX5day, and increased non-drought years in the late century relative to the baseline period. The study’s findings indicate that future conditions might be characterized by more rainy days but fewer large rainfall events; this might lead to a scenario of increased average annual rainfall but, at the same time, increased water scarcity during times of maximum demand. In the third and final study, the potential impact of climate change on hydrologic processes and droughts over the Kentucky River basin was studied using the watershed model Soil and Water Assessment Tool (SWAT). The SWAT model was successfully calibrated and validated and then forced with forecasted precipitation and temperature outputs from a suite of CMIP5 global climate model (GCMs) corresponding to two different representative concentration pathways (RCP 4.5 and 8.5) for two time periods: 2036-2065 and 2070-2099, referred to as mid-century and late-century, respectively. Climate projections indicate that there will be modest increases in average annual precipitation and temperature in the future compared to the baseline (1976-2005) period. Monthly variations of water yield and surface runoff demonstrated an increasing trend in spring and autumn, while winter months are projected as having decreasing trends. In general, maximum drought length is expected to increase, while drought intensity might decrease under future climatic conditions. Hydrological droughts (reflective of water availability), however, are predicted to be less intense but more persistent than meteorological droughts (which are more reflective of only meteorological variables). Results of this study could be helpful for preparing any climate change adaptation plan to ensure sustainable water resources in the Kentucky River Basin

Evaluation of APEX for Simulating the Effects of Tillage Practices in tropical soils

Tillage practices on agricultural fields have an impact on not only the amount of soil erosion from the fields, but also on the hydrologic and other environmental characteristics of the land. This erosion takes away soil that is necessary for sustainable agriculture, and the sediment and nutrient removal from the fields can pollute surrounding waterbodies. The Llanos Orientales of Colombia used to be a region of extended savannas and native fragile ecosystems dedicated to extended cattle ranch that has been transitioning to crop production. Agricultural expansion in this area, involving mechanization, could importantly accelerate the degradation of soils, limiting the development of sustainable agricultural systems. As a first step to understand long term effects of different tillage practices on new agricultural areas in the region, this study aims to evaluate the performance of the Agricultural Policy Environmental eXtender (APEX) model to simulate runoff, soil erosion and crop yield from fields under conventional tillage, reduced tillage, and no tillage in the Llanos Orientales of Colombia. Calibrated APEX model predictions were compared against measured runoff, soil loss and crop yield data from row crop plots established in the Experimental Station la Libertad in Colombia under conventional, reduced and no-tillage management. APEX satisfactorily predicted runoff (Nash Sutcliffe Efficiency NSE\u3e0.53, Percent Bias - [PBIAS] \u3c 21%) and crop yield for all three tillage systems (NSE\u3e0.82, [PBIAS] \u3c15%), but was not successful in predicting soil loss from the studied plots. Unsuccessful results were related to model limitations to predict erosion (USLE equations), but also to any uncertainty attributed to issues in the data collection. A calibrated APEX model could be used to predict runoff and crop yield responses under different management practices in the Llanos Orientales of Colombia, but needs improvements for prediction of soil erosion in tropical soils

Greenland Ice sheet [in "State of the Climate in 2017"]

peer reviewe

Water Resource Variability and Climate Change

Climate change affects global and regional water cycling, as well as surficial and subsurface water availability. These changes have increased the vulnerabilities of ecosystems and of human society. Understanding how climate change has affected water resource variability in the past and how climate change is leading to rapid changes in contemporary systems is of critical importance for sustainable development in different parts of the world. This Special Issue focuses on “Water Resource Variability and Climate Change” and aims to present a collection of articles addressing various aspects of water resource variability as well as how such variabilities are affected by changing climates. Potential topics include the reconstruction of historic moisture fluctuations, based on various proxies (such as tree rings, sediment cores, and landform features), the empirical monitoring of water variability based on field survey and remote sensing techniques, and the projection of future water cycling using numerical model simulations