Climatic trends in most parts of the world show a significant increase in rainfall amount, intensity and its frequency. Similarly, these trends are likely to continue in future as well. The major catastrophe caused by these rainfall trends comes as flooding, which is getting harder to predict, and mainly over the mountainous regions. Modelling these extreme rainfall events is crucial, which needs better forecasting skills and more understanding of existing Numerical Weather Prediction (NWP) modelling setup. Although, recent developments in NWP models increase the capabilities to simulate rainfall more precisely but the strengths and weaknesses of model need to be evaluated based on climatic conditions, terrain characteristics -- which include landuse, topography, new physical schemes and static datasets. Therefore, we have conducted comprehensive sensitivity and qualitative analysis with a numerous model setup, physical schemes and terrain datasets. / We contemplate various physical parameterizations and updated terrain datasets to simulate the rainfall over the complex topography using WRFV3-ARW modelling system. Additionally, the impact of topography and landuse on rainfall are discussed in detail along with a several combinations of newly available land surface, planetary boundary layer (PBL), cumulus, and cloud microphysics (MP) schemes. As a case study, we select the north region of Pakistan, which includes Khyber-Pakhtunkhwa (KPK) province and part of Hindukush-Karakoram-Himalaya (HKH), and this region have diversified the landscape and complex topographic features. For the sake of better understanding and comparative discussions, we study three extreme rainfall events; two of them occurred during monsoon period (i.e., July), while one in post monsoon period (i.e., September). / WRF-ARW 3.5.1 model is tuned and tested with GFS0.5 and CFSR/CFSv2 as forcing and lateral boundary conditions with a number of parameterization schemes. Similarly, to minimize the errors induced by terrain features, we apply wind correction and drag parameterizations. Furthermore, 3-arc-second hydrologically corrected SRTM digital elevation model (DEM), modified MODIS IGBP 30-arc-second, MODIS 15-arc-second and GLCNMO2008 landuse datasets were also integrated to WRF along with default datasets in WRF modelling system. / We verify the simulated rainfall by using observed, the Tropical Rainfall Measuring Mission (TRMM) and the Climate Prediction Centre morphing method (CMORPH) rainfall datasets. The GIS-based verification technique, called fisher-net is also introduced which is more compatible and flexible with other tools as well. / 隨著全球氣候變化的加劇，強暴雨極端天氣事件呈現突發、多發、併發的特點，其頻次、強度、持續時間、籠罩範圍近年來均呈現急速上升的趨勢。如何構建高時效性、高精度和高可用的極端天氣事件模擬工具，已經成為災害應急管理與回應等領域迫切需要解決的關鍵科學問題。作為極端天氣事件類比的核心，數值氣象模型對極端暴雨事件的模擬能力日益完善；然而，到目前為止，氣象模型的可靠性和有效性評價仍是其推廣應用的關鍵，特別是如何顧及土地利用類型、地形、新型物理機制和多源靜態資料庫前提下的模型可靠性評價仍面臨很多挑戰。因此，本文提出了顧及不同物理機制、地形特徵的模型構建、模型敏感性評價和定量分析方法。 / 首先，本文在顧及不同的物理參數和地形特徵的基礎上，利用WRFV3-ARW 建模系統實現了對複雜地形特徵下降雨過程的類比與分析。在此基礎上，本文充分考慮和利用新的土地下墊面、行星邊界層、積雲以及雲微物理機制，以詳細分析了地形和土地利用類型對降雨影響。實驗選用具有複雜地形結構和特徵的巴基斯坦北部的Khyber-Pakhtunkhwa (KPK)省和部分Hindukush-Karakoram-Himalaya (HKH) 區域；為了獲取更充分的分析結果，本位對該實驗區域內三次極端降雨事件進行了模擬和分析，包括季風期（例如七月）的兩次降雨事件和季風期過後（例如九月）的一次降雨事件。 / 其次，本文利用GFS0.5 和 CFSR/CFSv2 作為強迫和側邊界條件，設置多參數方案對WRF-ARW 3.5.1 模型進行了優化和測試。與此同時，為了降低由地形特徵導致的類比誤差，本文引入了風向糾正參數和風阻參數。除此之外，本文充分利用了水文糾正過後的3 弧秒精度的SRTM DEM 資料、30 弧秒精度的MODIS IGBP 資料、15 弧秒精度的MODIS 資料、GLCNMO2008 格式的土地利用資料、以及WRF 建模系統的預設資料，支撐WRF 的建模過程。 / 最後，為了驗證本文實驗結果的可靠性，本文利用TRMM 獲取的實測降雨量資料以及TRMM 提供的降雨資料庫驗證，基於GIS 的漁網驗證法，對上述模擬結果進行了詳細的分析 / Sultan, Shahzad. / Thesis Ph.D. Chinese University of Hong Kong 2015. / Includes bibliographical references (leaves 111-125). / Abstracts also in Chinese. / Title from PDF title page (viewed on 09, September, 2016). / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only.

The West African Monsoon (WAM) is a significant component of the global monsoon system and plays a key role in the annual cycle of precipitation in the Sahel region of Africa (10°N to 20°N) during the summer months (July to September). Rainfall in the Sahel varies on timescales ranging from seasons to millennia as a result of changes in the WAM. In the last century, the Sahel experienced a relatively wet period (prior to the 1960s) followed by a period of severe drought (1970s-1980s) with higher-frequency variability superimposed on this low-frequency background signal. Understanding precipitation variability like that which occurred over the 20th Century and its impact on Sahel precipitation is critically important for skillful hydroclimate predictions and disaster preparedness in the region. Previous work has shown that the WAM responds to both internal atmospheric variability and external oceanic forcing. A large fraction of 20th Century Sahel rainfall variability has been linked to nearby and remote oceanic forcing from the Atlantic, Pacific, and Indian Oceans, suggesting that the ocean is the primary driver of variability. However, the mechanisms underlying the influence of sea surface temperature (SST) forcing to land based precipitation and the relative importance of the roles of different basins are not as well understood. To this end, the work completed in this thesis examines the physical mechanisms linking oceanic forcing to recent precipitation variability in the Sahel and identifies them alongside large-scale environmental conditions. A series of moisture budget decomposition studies are performed for the Sahel in order to understand the processes that govern regional hydroclimate variability on decadal and interannual time scales. The results show that the oceanic forcing of atmospheric mass convergence and divergence explains the moisture balance patterns in the region to first order on the timescales considered. On decadal timescales, forcing by the Indian and Atlantic Oceans correlate strongly with precipitation variability. The combination of a warm Indian Ocean and negative gradient across the Atlantic forces anomalous circulation patterns that result in net moisture divergence by the mean and transient flow. Together with negative moisture advection, these processes result in a strong drying of the Sahel during the later part of the 20th Century. Diagnosis of moisture budget and circulation components within the main rainbelt and along the monsoon margins show that changes to the mass convergence are related to the magnitude of precipitation that falls in the region, while the advection of dry air is associated with the maximum latitudinal extent of precipitation. On interannual timescales, results show that warm conditions in the Eastern Tropical Pacific remotely force anomalously dry conditions primarily through affecting the low-troposphere mass divergence field. This behavior is related to increased subsidence over the tropical Atlantic and into the Sahel and an anomalous westward flow of moisture from the continent, both resulting in a coherent drying pattern. The interannual signal is then further explored, particularly in light of the expected link between the El Niño Southern Oscillation and dry conditions in the Sahel, notably unseen during the historic El Niño event of 2015. Motivated by this, recent El Niño years and their precipitation signature in the Sahel along with the associated large-scale environmental conditions are examined. Two different outcomes for Sahel summer season are defined; an anomalously wet or an anomalously dry season coincident with El Niño conditions. The different precipitation patterns are distinguished by increased moisture supply for the wet years, which can be driven by both regional oceanic conditions that favor increased moisture convergence over the continent as well as weaker El Niño forcing. Finally, a series of new idealized SST-forced experiments that explore the causal link between oceanic forcing and the response of convection in the region on daily time resolution are discussed and preliminary results shown. These experiments aim to understand how convection in the Sahel responds to SST forcing using transient model simulations that track the evolving response of the WAM through time, day-by-day, under different oceanic conditions. Preliminary results show the stark differences in seasonal precipitation that occur when anomalies of opposite sign are applied in parts of the Atlantic and Pacific basin. There is also a suggestion of a difference in the timing of the rainy season when the model is run with different SST configurations.

Soil moisture estimates from space on a continuous spatial domain could afford researchers with insight about agricultural productivity, flood vulnerability, and biological processes. To evaluate satellite soil moisture estimates, the SMAPVEX-16 experiment was one of a suite of verification data collection campaigns for NASA’s Soil Moisture Active Passive satellite. Soil moisture and its role in rainfall partitioning are of great interest to researchers at the Iowa Flood Center [IFC], which was founded in Iowa City, Iowa after a devastating flood event in 2008. A network of two dual-pol capable X-band radar units owned by the IFC, as well as five tipping bucket rain gauges, complemented by 15 from the USDA’s Agricultural Research Service were deployed in Central Iowa from May to August 2016 to monitor precipitation on a fine spatiotemporal domain. The data from this particular experiment was analyzed. Several radar-rainfall algorithms were assembled with a focus on assimilating multivariate radar data. Different variables allow researchers to overcome problems due to signal attenuation by X-band radars, and process radar observations into rainfall accumulations by several methods popular in the literature. Special techniques for accumulating instantaneous rainfall rates at discrete observation intervals were employed to account for the movement of storms. The rain totals between the observation points were estimated and the accumulations were compared to the rain gauge totals. Methods of rain rate calculation that assimilate many sources of data, such as radar reflectivity, differential reflectivity, and specific differential phase shift yielded the best results.

Previous works have validated the concept of a microwave rain gauge that operates as follows. With a microwave Doppler motion sensor, the Doppler shift created by falling rain drops is measured. One can then relate the corresponding fall velocity to rain rate. However, the available Doppler motion sensors are lacking in several aspects. Here we address the important electronic design and signal processing considerations related to a microwave-based rain gauge.

From an agronomic perspective, the spreading of manure (sometimes containing antibiotics) onto agricultural fields is beneficial to the soil as a renewable source of fertilizer by increasing organic matter and providing nutrient inputs for crops. However, the use of antibiotics can be excessive, resulting in manures containing residual antibiotics contaminating soils and waterways. Thus, there is a need to improve existing or develop new management practices to minimize the losses of antibiotics from manure entering waterways and groundwater. Biochar is a carbon-rich material produced from the oxygen-free pyrolysis of biomass. Generally, biochars have high surface area and sorb organic compounds and trace metals; thus, it is reasonable to hypothesize that biochars sorb antibiotics. The main goal of this research was to investigate if incorporated biochar to soil facilitates the transport of antibiotics under simulated rainstorm events. The specific objectives were to investigate the losses of surface-applied antibiotics to soils with different (1) application rates of biochar and rainfall intensities, and (2) if the losses were antibiotic type-dependent. <br>

An extreme precipitation categorization scheme, developed to temporally and spatially visualize and track the multi-scale variability of extreme precipitation climatology, is introduced over the continental United States and used as the basis for an observational dataset intercomparison. The categorization scheme groups three-day precipitation totals exceeding 100 mm into five precipitation categories, or "P-Cats". To assess observational uncertainty across a range of precipitation measurement approaches, we compare in situ station data from the Global Historical Climatology Network-Daily (GHCN-D), satellite derived data from the Tropical Rainfall Measuring Mission (TRMM), gridded station data from the Parameter-elevation Regression on Independent Slopes Model (PRISM), global reanalysis from the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA 2), and regional reanalysis from the North American Regional Reanalysis (NARR). While all datasets capture the principal spatial patterns of extreme precipitation climatology, results show considerable variability across the five-platform suite in P-Cat frequency, spatial extent, and magnitude. Higher resolution datasets, PRISM and TRMM, most closely resemble GHCN-D and capture a greater frequency of high-end totals relative to lower resolution products, NARR and MERRA-2. When all datasets are regridded to a common coarser grid, differences persist with datasets originally constructed at a high resolution maintaining the highest frequency and magnitude of P-Cats. Potential future applications of this scheme include tracking change in P-Cats over space and time, climate model evaluation, and assessment of model projected change.

Microplastic pollution as a global environment problem in marine systems has substantially raised public concern in recent years. In 2016, the Swedish Environmental Protection Agency performed a study about potential sources and pathways of microplastics spreading to the marine environment. Microplastics from artificial turfs have been recognized as the second most important source of microplastic emission in Sweden. Between 1640 to 2460 tons per year of microplastics are estimated to be lost from artificial turfs. The lost microplastics are potentially transported to stormwater wells by runoff during rainfall events, eventually reaching marine environments. This study aims to track microplastics from artificial turfs to stormwater wells. Since the research of microplastic in stormwater has so far shown to be limited, field work and laboratory analysis have been developed in this study. Four artificial football fields located in Stockholm municipality were taken as sampling sites. First, pathways for microplastics from artificial turfs to stormwater were investigated. Second, the characteristics of microplastic granulates infill used in the football fields have been analyzed. Finally, stereo microscopy was used to visually identify microplastics in stormwater. The results showed that rainfall as a driving force of runoff process contributes to microplastics transport from artificial turfs to stormwater. During this transport process, a fraction of microplastics is captured by the soil. The size of microplastic granulates identified not only in stormwater but also in stormwater sediments is typically between 1 mm to 3 mm. Due to its limitations, stereo microscopy is quite a subjective method for identifying microplastics and thus not suitable for quantitative analysis, since microplastic particles are comparable in size to and visually difficult to differentiate from organic particles co-occurring in stormwater. In order to accurately quantify the amounts of microplastics transported to stormwater systems from artificial turfs, it is necessary to develop new methods for microplastics identification. This study presented an attempt in this direction, highlights its limitations, and discusses more suitable alternatives.

Radar-rainfall uncertainty quantification has been recognized as an intricate problem due to the complexity of the multi-dimensional error structure, which is also associated with space and time scale. The error structure is usually characterized by two moments of the error distribution: bias and error variance. Despite numerous efforts to investigate radar-rainfall uncertainties, many questions remain unanswered. This dissertation uses two statistical descriptions (mean and variance) of the error distribution to highlight and describe some of the remaining gaps in representing radar-rainfall uncertainties. The four central issues addressed in this dissertation include: 1. Investigation of radar relative bias caused by radar calibration. 2. Statistical modeling of range-dependent error arising from the radar beam geometry structure. 3. Scale-dependent variability of radar-rainfall and rain gauge error covariance. 4. Scale-dependence of radar-rainfall error variance. The first two issues describe systematic features of main error sources of radar-rainfall. The other two are associated with quantifying radar error variance using the error variance separation (EVS) method, which considers the spatial sampling mismatch between radar and rain gauge data. This study captures the main systematic features (systematic bias arising from radar calibration and range-dependent errors) of radar measurements without using ground reference data and the error variance structure with respect to the spatio-temporal transformation of the measurements for further applications to hydrologic fields. Such consideration of radar-rainfall uncertainties represented by error mean and variance can enhance the characterization of the uncertainty structure and yield a better understanding of the physical process of precipitation.

The study of soil erodibility has become of paramount interest in the last few decades. The effects of soil erosion are serious and extensive and affect nearly all people.

>Magister Scientiae - MSc / The current study aimed at providing groundwater recharge estimates in a fractured rock aquifer environment that is occupied by pine plantation and indigenous forests in order to improve the understanding of the effect of pine plantation forests on recharge. This was based on the argument that for the trees to affect recharge, they do not necessarily need to tap directly from the saturated zone, as vegetation may indirectly affect groundwater recharge by interception and abstracting the infiltrating water in the vadose zone before reaching the water table. The study was conducted along the Southern Cape coastline of Western Cape Province in South Africa. This area is 7 km east of George in an area characterized by the occurrence of the Table Mountain Group aquifer. The research presented in this thesis formed part of a Water Research Commission (WRC) project titled “The Impacts of Commercial Plantation Forests on Groundwater Recharge and Streamflow”. To achieve the aim of the current study, three objectives were formulated: i) to characterize the dominantly occurring recharge mechanism ii) to determine long-term groundwater recharge estimates, and iii) to assess the effect of plantation forests on groundwater recharge. As part of characterizing the dominant recharge mechanism in the area, a conceptual groundwater recharge model of the area was developed to explain the recharge mechanism and facilitate an improved understanding of recharge estimates. The model was based on a theoretical understanding and previous investigations conducted in the study area. Methods such as environmental stable isotopes and hydrochemistry were used to refine the conceptual model by identifying the source of recharge and the dominant recharge mechanism. The occurrence and density of lineaments were used as a proxy to delineate potential recharge zones in the area. Recharge was estimated using the Rainfall Infiltration Breakthrough (RIB) and the Chloride Mass Balance (CMB) methods. Additionally, the effect of plantation forests on recharge was assessed using the HYDRUS-2D numerical model. The recharge estimates derived from the RIB and CMB techniques were verified using the published maps by Vegter (1995).