Spatial Variability Of Rainfall Research Articles

Growth and production of colored fiber cotton (Gossypium hirsutum L.) subjected to salt stress and potassium fertilization

Temporal and spatial variation of rainfall in semiarid regions may lead to an increase in the concentrations of salts present in irrigation water, and it is necessary to adopt techniques to reduce the negative effects of salts on plants. Thus, the present study aimed to evaluate the growth and production of colored cotton cv. BRS Topázio as a function of irrigation using water with different levels of salinity and potassium doses. The experiment was carried out in pots adapted as lysimeters under greenhouse conditions, using a non-saline Neossolo Regolítico (Entisol) of sandy texture. The experimental design was randomized blocks, with 4 replicates, with treatments distributed in a 4 x 4 factorial scheme, corresponding to four levels of saline irrigation water electrical conductivity (1.5; 3.0; 4.5 and 6.0 dS m-1) and four potassium doses (50; 75; 100 and 125% of the recommendation), with a dose of 100% corresponding to 150 mg K2O per kg-1 of soil. Irrigation using water of electrical conductivity (saline) above 1.5 dS m-1 negatively affected the growth and production of cotton cv. BRS Topázio, and cotton seed weight was the most sensitive variable. Potassium doses above 50% of the recommendation in interaction with salinity reduced the height and leaf area of cotton cv. BRS Topázio.

A Robust Method to Update Local River Inundation Maps Using Global Climate Model Output and Weather Typing Based Statistical Downscaling

Global warming is changing the magnitude and frequency of extreme precipitation events. This requires updating local rainfall intensity-duration-frequency (IDF) curves and flood hazard maps according to the future climate scenarios. This is, however, far from straightforward, given our limited ability to model the effects of climate change on the temporal and spatial variability of rainfall at small scales. In this study, we develop a robust method to update local IDF relations for sub-daily rainfall extremes using Global Climate Model (GCM) data, and we apply it to a coastal town in NW Spain. First, the relationship between large-scale atmospheric circulation, described by means of Lamb Circulation Type classification (LCT), and rainfall events with potential for flood generation is analyzed. A broad ensemble set of GCM runs is used to identify frequency changes in LCTs, and to assess the occurrence of flood generating events in the future. In a parallel way, we use this Weather Type (WT) classification and climate-flood linkages to downscale rainfall from GCMs, and to determine the IDF curves for the future climate scenarios. A hydrological-hydraulic modeling chain is then used to quantify the changes in flood maps induced by the IDF changes. The results point to a future increase in rainfall intensity for all rainfall durations, which consequently results in an increased flood hazard in the urban area. While acknowledging the uncertainty in the GCM projections, the results show the need to update IDF standards and flood hazard maps to reflect potential changes in future extreme rainfall intensities.

Spatiotemporal variability and trends in rainfall and temperature in Alwero watershed, western Ethiopia

Climate analysis at relevant time scales is important for water resources management, agricultural planning, flood risk assessment, ecological modeling and climate change adaptation. This study analyses spatiotemporal variability and trends in rainfall and temperature in Alwero watershed, western Ethiopia. Our analysis is focused on describing spatial and temporal variability of rainfall in the study area including detection of trends, with no attempt at providing meteorological explanations to any of the patterns or trends. The study is based on gridded monthly rainfall and maximum and minimum temperature data series at a resolution of 4 × 4 km which were obtained from the National Meteorological Agency of Ethiopia for the period 1983–2016. The study area is represented by 558 points (each point representing 4 × 4 km area). Mean annual rainfall of the watershed is > 1600 mm. Annual, June–September (Kiremt), March–May (Belg) rainfall totals exhibit low inter-annual variability. Annual and October-February (Bega) rainfalls show statistically significant increasing trends at p = 0.01 level. May and November rainfall show statistically significant increasing trends at p = 0.01 level. March shows statistically significant decreasing trend at p = 0.1 level. The mean annual temperature of the watershed is 25 °C with standard deviation of 0.31 °C and coefficient of variation of 0.01 °C. Mean annual minimum and maximum temperatures show statistically non-significant decreasing trends. Bega season experienced statistically significant deceasing trend in the maximum temperature at p = 0.01 level. The year-to-year variability in the mean annual minimum and maximum temperatures showed that the 2000s is cooler than the preceding decades. Unlike our expectations, annual and seasonal rainfall totals showed increasing trends while maximum and minimum temperatures showed decreasing trends. Our results suggest that local level investigations such as this one are important in developing context-specific climate change adaptation and agricultural planning, instead of coarse-scale national level analysis guiding local level decisions.

A Comparative Evaluation of the Performance of CHIRPS and CFSR Data for Different Climate Zones Using the SWAT Model

The spatial and temporal scale of rainfall datasets is crucial in modeling hydrological processes. Recently, open-access satellite precipitation products with improved resolution have evolved as a potential alternative to sparsely distributed ground-based observations, which sometimes fail to capture the spatial variability of rainfall. However, the reliability and accuracy of the satellite precipitation products in simulating streamflow need to be verified. In this context, the objective of the current study is to assess the performance of three rainfall datasets in the prediction of daily and monthly streamflow using Soil and Water Assessment Tool (SWAT). We used rainfall data from three different sources: Climate Hazards Group InfraRed Rainfall with Station data (CHIRPS), Climate Forecast System Reanalysis (CFSR) and observed rain gauge data. Daily and monthly rainfall measurements from CHIRPS and CFSR were validated using widely accepted statistical measures, namely, correlation coefficient (CC), root mean squared error (RMSE), probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI). The results showed that CHIRPS was in better agreement with ground-based rainfall at daily and monthly scale, with high rainfall detection ability, in comparison with the CFSR product. Streamflow prediction across multiple watersheds was also evaluated using Kling-Gupta Efficiency (KGE), Nash-Sutcliffe Efficiency (NSE) and Percent BIAS (PBIAS). Irrespective of the climatic characteristics, the hydrologic simulations of CHIRPS showed better agreement with the observed at the monthly scale with the majority of the NSE values ranging between 0.40 and 0.78, and KGE values ranging between 0.62 and 0.82. Overall, CHIRPS outperformed the CFSR rainfall product in driving SWAT for streamflow simulations across the multiple watersheds selected for the study. The results from the current study demonstrate the potential of CHIRPS as an alternate open access rainfall input to the hydrologic model.

Seasonality in power law scaling of convective and stratiform rainfall with lightning intensity over Indian Monsoon regions

The power law relationship between the rain (RT) and lightning flash (LF) is useful for estimating rainfall over poorly gauged catchment areas of rivers over north-east India (NEI) and that between LF and storm top height (STH) is key to lightning parametrization in models. However, they are poorly constrained over the Indian monsoon region where potential for significant changes exists with large spatial variability of rainfall, strong land-ocean contrast, seasonality and contribution of stratiform to total rainfall. Using 16 years of TRMM-PR data and LIS data, here we examine the RT and LF relationship and between LF and STH during pre-monsoon and monsoon seasons over four regions, NEI, Central India (CI), Bay of Bengal (BoB) and Indian Ocean (IO). A stronger power law (exponent b = 0.71) during pre-monsoon than that during the monsoon season (b = 0.58) apply for convective rain over land (including BoB) while a weaker relationship is applicable for stratiform rain with b = 0.60, and b = 0.47 respectively. Over IO, the relationship is nearly identical for convective and stratiform rain with no seasonality (b ~ 0.4). A power law poorly represents the LF-STH relationship over land and fails over IO. A fifth power law is applicable only for pre-monsoon convective rain over land weakening to half in monsoon seasons (b = 2.48). For stratiform rain it is weaker with (b = 3.27) and (b = 1.67) for pre-monsoon and monsoon seasons respectively. Our findings suggest that one threshold based lightning parameterizations are inadequate and need to be generalized to include regional and seasonal differences unraveled here.

Application of high-resolution meteorological data from NCAM-WRF to characterize agricultural drought in small-scale farmlands based on soil moisture deficit

We discussed the applicability of high-resolution meteorological data simulated by the NCAM-Weather Research and Forecasting (NCAM-WRF) model to investigate spatially distributed soil-moisture deficits in site-scale farmland areas. A gridded soil water budget model was developed to utilize the 90 m NCAM-WRF meteorological data to predict soil moisture content (SMC) at multiple depths. The applicability of the NCAM-WRF climatic variables to predict SMC was evaluated by comparing the SMC estimates with in-situ observations at the monitoring site. We used the Quantile Mapping (QM) method to correct the biases of NCAM-WRF precipitation outputs. The SMC estimates derived from the newly developed soil water budget model showed a good agreement with observations, and we proved that the bias-corrected NCAM-WRF precipitation data could improve the predictability of the temporal evolution of SMCs. For characterizing agricultural drought during the crop growing season, we presented a novel approach to estimate the magnitude, duration, and severity of agricultural drought events based on crop's critical pressure head. We mapped the distribution of SMC, soil matric potential (SMP), and drought severity at the 90-m resolution, and the results showed that applying the NCAM-WRF climatic variables to the modeling of SMC/SMP profiles can lead to drought characterization on site-scale while accounting for the spatial variability of rainfall and other climatic variables.

Study of the spatial and temporal variability of rainfall in the Middle and Lower Cheliff (Algeria)

Abstract. The purpose of this study is to identify homogeneous rainfall regions and to study the spatial and temporal variability of rainfall in the Cheliff basin using the regional vector method and the statistical approach (Pettitt test, Lee Heghinian test and Hubert segmentation) and the geostatistic approach (inverse distance weighting method). In terms of results, the regional vector method highlighted six (6) homogeneous rainfall regions. The downward trend occurred in the study area in 1972, affecting a few coastal stations. In 1976, this decline extended to the South West and throughout the coastal region. In 1980, the drop covered the entire basin. This decline has resulted in an estimated deficit of 30 % on average in the eastern region, the coastal region and the Mina. However, the central part of the basin experienced a 20 % decrease compared to the period before the break (1968–1980). The same spatial irregularity in rainfall was observed during the pre-break and post-break periods (1981–2010). On the other hand, throughout the basin, the areas corresponding to the rainfall ranges identified during the 1968–1980 period experienced an average decrease of 100 mm during the post-break period, except in the eastern region, where the decrease exceeded 200 mm.

Spatiotemporal dynamics of rainfall in Upper East Region of Ghana, West Africa, 1981–2016

There has been an increasing concern about effects of global warming on rainfall. Negative impacts on rainfall affect the environment and socio-economic activities of nations, globally. Rainfall characteristics at the Upper East Region (UER) of Ghana in terms of temporal and spatial variability are investigated from 1981 to 2016 using rainfall data from Ghana Meteorological Agency (GMet) and Climate Hazards Group Infrared Precipitation with Station. Using cumulative residual analysis, Mann–Kendall (MK), Sen’s slope, wavelet transform (WT) and principal component analysis (PCA) tests, the rainfall variability in UER was examined. Results showed that 1981, 1999, 2002 and 2013 were years of major changes in rainfall variation. The MK and Sen’s slope showed that 55.71% of UER have decreasing monthly rainfall with 27.34% significant trend. Months April, May and June showed decreasing rainfall trends. Months July, August and September showed significant increasing rainfall trend. WT revealed a significant variation in the annual rainfall. PCA revealed that the spatial variability of rainfall in UER is very diverse with 33.76% of the variability located in the northeastern part. The findings serve as benchmark in providing in-depth understanding of rainfall variation in UER for water resource managers, agriculturalists and drought mitigation.

The Influence of Subsurface Conditions on the Spatial and Temporal Variability of Tropical SST and Rainfall in CFSv2 Reforecasts

AbstractThis study examines the potential impact of subsurface potential temperature and current conditions on the sea surface temperature (SST) and rainfall over the tropical region using Climate Forecast System Version 2 (CFSv2) ensemble seasonal reforecasts for 1958–2014. The climatological difference of earlier period (1958–78; P58‐78) and later period (1994–2014; P94‐14) in January initialized reforecasts (JIR) depicts mild‐warm SST over the equatorial eastern Pacific in January, but its magnitude becomes larger over there from May to August. The difference between JIR P58‐78 and P94‐14 depicts warm potential temperature (PT) up to 3°C over the equatorial central and eastern Pacific at depth from 155 to 70 m in January therefore 20°C isotherm of JIR P58‐78 in January tends to be deeper in the equatorial eastern Pacific than JIR P94‐14. The magnitude of equatorial undercurrent (EUC) in JIR P58‐78 is larger in the eastern Pacific at depth from 125 to 35 m from January to February than JIR P94‐14. Therefore, water upwelled to the surface through EUC was usually warm in January of JIR P58‐78. As lead months increase, the center of warm PT gradually moves upward in the eastern Pacific than its location in January, resulting in development of warm SST in the eastern Pacific in March. The difference between April initialized reforecasts P58‐78 and P94‐14 depicts warm PT up to 1.5°C in the eastern Pacific at depth from 135 to 35 m in April but as lead months increase, magnitude of warm PT gradually decreases, resulting in negligible difference SST over the eastern Pacific.

Clinical and epidemiological profile of patients admitted with dengue fever in a tertiary care hospital, Thrissur, Kerala, India

Background: Dengue is a fast emerging mosquito borne pandemic prone viral disease affecting many parts of the world. The elucidation of the exact clinical profile is important for patient management and thus crucial for saving life. Dengue is widespread throughout the tropics, with risk factors influenced by local spatial variations of rainfall, temperature, relative humidity, degree of urbanization and quality of vector control.Methods: A descriptive study was undertaken and data was collected by reviewing the records of patients admitted with dengue fever over a period from January 2019 to August 2019. Total 100 records of confirmed cases of dengue were included in the study. The information regarding demographic details, clinical symptoms and complications, and epidemiological details were collected from the records using a questionnaire. Results: Out of 100 patients admitted with dengue, 61% were males and 54% of the total were admitted during June and July month. Most common symptoms reported were fever (99%), headache (91%), muscle & joint pain (71%). The bleeding manifestation was reported in 11% and the most common site of bleeding was gastrointestinal tract.Conclusions: The present study concludes that dengue confirmed cases are seen more among males, and the incidence of disease is more in age groups of less than 30 years. Most of them were residing in the Northern part of Thrissur (56%) and the most common clinical symptoms were fever and headache.

Characterization of Spatio-Temporal Trends and Periodicity of Precipitation over Malawi during 1979–2015

Precipitation remains the key climatic parameter in sub-Saharan Africa, as it drives the economy through rain-fed agricultural production. Malawi is one of the countries most susceptible to the impacts of climate change and variability. This paper presents the characteristics of spatio-temporal trends and periodicity of precipitation in Malawi in the period from 1979 to 2015. The analysis was based on recent rain ground gauge data. In total, 31 out of 36 rainfall stations, which include some key stations from the southeast of Malawi, were selected for the study after robust homogeneity tests were applied to the datasets. Spatial distribution of annual mean precipitation showed that high amounts of rainfall are located in areas along the lake and the southeast part of Malawi. The spatial distribution of the wet season (November to April) precipitation from EOF (Empirical Orthogonal Function) analysis revealed ten wet years (1985, 1986, 1989, 1996, 1997, 1999, 2001, 2006, 2007, and 2015) and ten dry years (1981, 1983, 1987, 1990, 1992, 1994, 1995, 2005, 2011, and 2014). In general, the temporal trends analyses of seasonal (wet season) and annual precipitations both displayed slight decreasing slopes during the 37 years. The trend of precipitation per decade displayed an increase in precipitation during 1980s and 1990s, followed by a decrease in the 21st century. Furthermore, the analysis of the spatial and temporal variability and trends of rainfall showed that northern and central Malawi displayed a clearer variability than southern Malawi. Although the trends of most of the stations are not significant at 95% confidence level, the decreasing rates of rainfall in the last decade and the decreasing trends on wet season and annual scale detected by Mann–Kendall tests require closer monitoring of rainfall changes in the near future. The stations which exhibited significant trends (Naminjiwa and Dedza stations) also call for closer monitoring, since the area relies heavily on rain-fed agriculture for economic sustenance.

Sensitivity of Grapevine Soil–Water Balance to Rainfall Spatial Variability at Local Scale Level

In rainfed agriculture systems, rainfall water management (harvesting, storage and efficient use) is a key issue. At local scale (i.e. from 100m to 50 km), the impact of rainfall space and time variability on crop water availability is seldom addressed. In order to accurately depict the space and time variations of rainfall at local scale, a dense rain-gauges network composed of 45 rain-gauges has been deployed over 28 km² area, in Burgundy vineyards (North-East France). Rainfall data collected by each rain-gauge from 2014 to 2016 was used as input variables in the grapevine water balance model proposed by Lebon et al. All other climate variables, vineyard and soil parameters were kept strictly identical for each simulation in order to capture the consequences of the sole spatial variability of rainfall on vineyard water status. As rainfall dynamics impact on the vineyard depends on the soil water content, water balance was modelled considering soils with low (50 mm) and medium (150 mm) soil water holding capacities, representative of the soils of the area. The impact of modelled soil water availability for grapevine was assessed using the water deficit stress index (WDSI), i.e. the relative stomatal conductance. Local rainfall variability throughout the vine vegetative period lead to large variations in WDSI: it varied up to 0.3 within the study area solely because of rainfall spatial variability. Using a set of 34 weather stations at mesoscale level over Burgundy (186 km from North to South), we showed that local rainfall might contribute to change in grapevine water status as large as 50% of the simulated regional water balance spatial variability. Our results indicates that local rainfall and its impacts on agricultural production are probably not sufficiently considered in farming systems, potentially leading to in-accurate water management (cover-crop, irrigation) due to sparse rainfall network.

Evidence of Abrupt Climate Change during the Mid‐ to Late‐Holocene Recorded in a Tropical Lake, Southern China

AbstractResearch on abrupt paleoclimatic and paleoenvironmental change provides a scientific basis for evaluating future climate. Because of spatial variability in monsoonal rainfall, our knowledge about climate change during the mid‐ to late‐Holocene in southern China is still limited. We present a multi‐proxy record of paleoclimatic change in a crater lake, Lake Shuangchi. Based on the age‐depth model from 210Pb, 137Cs and AMS14C data, high‐resolution mid‐ to late‐ Holocene climatic and environmental records were reconstructed using multiple indices (TOC, TN, C/N, δ13C and grain size). Shuangchi underwent a marked change from a peat bog to a lake around 1.4 kaBP. The C3 plants likely dominated during 7.0–5.9 ka and 2.5–1.4 kaBP, while C4 plants dominated between 5.9–3.2 and 3.0–2.5 kaBP. Algae were dominant sources of organic matter in the lake sediments after 1.4 kaBP. Several intervals with high concentrations of coarser grain sizes might be due to flood events. These results reveal that several abrupt paleoclimatic events occurred around 6.6 ka, 6.1 ka, 5.9 ka, 3.0 ka, 2.5 ka and 1.4 kaBP. The paleoclimatic change recorded in the lake may be related to the migration of the Intertropical Convergence Zone (ITCZ) and El Niño ‐ Southern Oscillation (ENSO) activity.

Exploring seasonality and erosivity of rainfall over a lower Himachal Himalayan catchment, India

The present study aims to explore the spatial distribution and trends in rainfall, its seasonality and erosivity between 1971 and 2015 over the Suketi river catchment of lower Himachal Himalayas in India. Daily rainfall recorded at three stations in the catchment have been used for the computation of rainfall seasonality and erosivity by employing non-parametric indices say seasonality index, precipitation concentration index and modified Fournier index. The distribution maps have been prepared by applying the kriging technique of geographic information system. The results have indicated remarkable spatial and temporal variability in rainfall as well as in its seasonality and erosivity. Largely, the pattern of rainfall has been found unimodal (single wet season) and more than 95% area of the catchment have witnessed a marked seasonality and prevalence of very severe rainfall erosivity. However, the long-term annual rainfall erosivity has revealed a statistically non-significant decreasing trend. The highest values of rainfall erosivity have been observed in the month of July followed by August, June and September with lower reaches being the most vulnerable one. We have witnessed an absolute relationship between annual rainfall and modified Fournier index (R2 = 0·999; p < 0·001), indicating that the spatial distribution of annual rainfall erosivity is intensely controlled by annual rainfall depth. Finally, it is hoped that the results of this study will assist farmers, agronomists and policy makers in chalking out best management practices for reducing soil erosion vulnerability not only for the Suketi river catchment but also for other identical catchments of the lower Himachal Himalayas.

Monitoring Residual Soil Moisture and Its Association to the Long-Term Variability of Rainfall over the Upper Blue Nile Basin in Ethiopia

Monitoring soil moisture and its association with rainfall variability is important to comprehend the hydrological processes and to set proper agricultural water use management to maximize crop growth and productivity. In this study, the European Space Agency’s Climate Change Initiative (ESA CCI) soil moisture product was applied to assess the dynamics of residual soil moisture in autumn (September to November) and its response to the long-term variability of rainfall in the Upper Blue Nile Basin (UBNB) of Ethiopia from 1992 to 2017. The basin was found to have autumn soil moisture (ASM) ranging from 0.09–0.38 m3/m3, with an average of 0.26 m3/m3. The ASM time series resulted in the coefficient of variation (CV) ranging from 2.8%–28% and classified as low-to-medium variability. In general, the monotonic trend analysis for ASM revealed that the UBNB had experienced a wetting trend for the past 26 years (1992–2017) at a rate of 0.00024 m3/m3 per year. A significant wetting trend ranging from 0.001 to 0.006 m3/m3 per year for the autumn season was found. This trend was mainly showed across the northwest region of the basin and covers about 18% of the total basin area. The spatial patterns and variability of rainfall and ASM were also found to be similar, which implies the strong relationship between rainfall and soil moisture in autumn. The spring and autumn season rainfall explained a considerable portion of ASM in the basin. The analyses also signified that the rainfall amount and distribution impacted by the topography and land cover classes of the basin showed a significant influence on the characteristics of the ASM. Further, the result verified that the behavior of ASM could be controlled by the loss of soil moisture through evapotranspiration and the gain from rainfall, although changes in rainfall were found to be the primary driver of ASM variability over the UBNB.

Tropical rainfall trend and stationarity analysis

Abstract Climate change is most likely to cause changes to the temporal and spatial variability of rainfall. A trend analysis to investigate the rainfall pattern can detect changes over temporal and spatial scales for a rainfall series. In this study, trend analysis using the Mann–Kendall test and Sen's slope estimator was conducted in the Kelantan River Basin, Malaysia. The Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test was applied to evaluate the stationarity of the rainfall series. This basin annually faces onslaughts of varying year-end flooding conditions. The trend analysis was applied for monthly, seasonal and yearly rainfall series between 1989 and 2018. The temporal analysis results showed that both increasing and decreasing trends were detected for all rainfall series. The spatial analysis results indicated that the northern region of the Kelantan River Basin showed an increasing trend, whilst the southwest region showed a decreasing trend. It was found that almost all the rainfall series were stationary except at two rainfall stations during the Inter Monsoon 1, Inter Monsoon 2 and yearly rainfall series. Results obtained from this study can be used as reference for water resources planning and climate change assessment.

Spatial and Temporal Variation of Rainfall and Streamflow in the Kikuletwa Catchment of Upper Pangani Basin, Tanzania

Streamflow and rainfall records from 1980 to 2015 as a (common period for the analyzed stations) were used to analyze the variations of rainfall and streamflow in the Kikuletwa catchment. Also, the analysis of the longest time series available at each station up to 2015 (referred to as the whole series in this study) was conducted to relate past rainfall and streamflow changes, at the tributaries of Kikuletwa River located above the Rundugai natural springs as recommended from previous studies. Various methods such as simple statistics of the mean, standard deviation, coefficient of variance, and graphs were used to analyze intra-annual variations. Multi-year variability was analyzed by trends and change point tests using MannKendall and Pettitt tests respectively. The results of the study revealed the spatial variation of rainfall which was related to elevation differences. The streamflow amounts were found to vary from upstream to downstream. The whole time series analysis of annual rainfall and streamflow amounts revealed a decrease in rainfall and streamflow amounts for almost all stations though a significant decrease was only observed at two stations located on the upstream (for rainfall) and two stations located above the Rundugai natural springs (for streamflow). During 1980 – 2015, trends analysis indicated significant decreasing trends only in annual rainfall amounts at the two stations located on the upstream of the catchment with Z values of -3.20 and -2.68. In contrast, average annual flow trends analysis indicated significant decreasing trends at four stations out of five with Z values of -2.52, -2.28, -1.99 and -3.4 and, at one station insignificant decreasing trend was observed. The findings revealed the existence of other catchment influences to the streamflow changes other than rainfall during 1980-2015. The study provides very useful information that decides the necessity for separating the climate and human influences to the streamflow changes to find the most influencing factor.

Exploring the Clustering Property and Network Structure of a Large-Scale Basin’s Precipitation Network: A Complex Network Approach

Understanding of the spatial connections in rainfall is a challenging and essential groundwork for reliable modeling of catchment processes. Recent developments in network theory offer new avenues to understand of the spatial variability of rainfall. The Yellow River Basin (YRB) in China is spatially extensive, with pronounced environmental gradients driven primarily by precipitation and air temperature on broad scales. Therefore, it is an ideal region to examine the availability of network theory. The concepts of clustering coefficient, degree distribution and small-world network are employed to investigate the spatial connections and architecture of precipitation networks in the YRB. The results show that (1) the choice of methods has little effect on the precipitation networks, but correlation thresholds significantly affected vertex degree and clustering coefficient values of precipitation networks; (2) the spatial distribution of the clustering coefficient appears to be high–low–high from southeast to northwest and the vertex degree is the opposite; (3) the precipitation network has small-world properties in the appropriate threshold range. The findings of this paper could help researchers to understand the spatial rainfall connections of the YRB and, therefore, become a foundation for developing a hydrological model in further studies.

Developing Operation Procedures for Individual Reservoirs in a Large Multistate River Basin in Context of Tribunal Awards

The uncertain nature of monsoon and the high temporal and spatial variability of rainfall in India make it imperative to utilize the available water resources optimally and efficiently. Reservoirs are one of the most effective means of matching the temporal and spatial availability of water with demands. In India, the state governments are considered custodians of the water in their respective states. Sometimes, water-sharing disputes arise in large river basins that are shared by multiple states. A mechanism to resolve such disputes is through tribunals, which allocate the basin waters to different states and projects in accordance with their past and projected demands, water availability at different dependability levels, and other constraints. In such basins, the operation of individual projects/reservoirs, so as to follow all the stipulations of the tribunal, is a challenging task. In this paper, a methodology has been framed to develop the operation procedure for individual projects so as to honor the tribunal awards. The Krishna River basin in India has been used as an example case study. The proposed procedure keeps track of the total inflows received, the total water used, and the balance utilizations to be made at each project, each state, and the whole river basin in real time. Using this procedure, the percent utilization achieved by different sharing states of the Krishna basin, especially in deficit years, is quite close to the values specified by the tribunal. The developed methodology is quite general and can be applied to any river basin with suitable modifications.

Relationship of Weather Types on the Seasonal and Spatial Variability of Rainfall, Runoff, and Sediment Yield in the Western Mediterranean Basin

Rainfall is the key factor to understand soil erosion processes, mechanisms, and rates. Most research was conducted to determine rainfall characteristics and their relationship with soil erosion (erosivity) but there is little information about how atmospheric patterns control soil losses, and this is important to enable sustainable environmental planning and risk prevention. We investigated the temporal and spatial variability of the relationships of rainfall, runoff, and sediment yield with atmospheric patterns (weather types, WTs) in the western Mediterranean basin. For this purpose, we analyzed a large database of rainfall events collected between 1985 and 2015 in 46 experimental plots and catchments with the aim to: (i) evaluate seasonal differences in the contribution of rainfall, runoff, and sediment yield produced by the WTs; and (ii) to analyze the seasonal efficiency of the different WTs (relation frequency and magnitude) related to rainfall, runoff, and sediment yield. The results indicate two different temporal patterns: the first weather type exhibits (during the cold period: autumn and winter) westerly flows that produce the highest rainfall, runoff, and sediment yield values throughout the territory; the second weather type exhibits easterly flows that predominate during the warm period (spring and summer) and it is located on the Mediterranean coast of the Iberian Peninsula. However, the cyclonic situations present high frequency throughout the whole year with a large influence extended around the western Mediterranean basin. Contrary, the anticyclonic situations, despite of its high frequency, do not contribute significantly to the total rainfall, runoff, and sediment (showing the lowest efficiency) because of atmospheric stability that currently characterize this atmospheric pattern. Our approach helps to better understand the relationship of WTs on the seasonal and spatial variability of rainfall, runoff and sediment yield with a regional scale based on the large dataset and number of soil erosion experimental stations.