Spatial Variability Of Precipitation Research Articles

Effects of rainfall manipulations versus a natural aridity gradient on plant litter arthropods in desert and Mediterranean ecosystems

Predicting responses of litter arthropods to future variation in precipitation is critical for understanding decomposition processes under global climate change. A field experiment on litter arthropods extracted from litterbags using Berlese-Tullgren funnels was conducted under simulated drought and increasing precipitation treatments at a semiarid site and a Mediterranean site, and along a natural climatic gradient from arid to mesic Mediterranean ecosystems during three consecutive years. Our objective was to examine the effects of variation in water availability on the abundance of litter arthropods along the aridity gradient. The results demonstrated positive responses of total abundances, including Acari abundance, but negative responses of taxonomic richness to experimentally increased precipitation at the semiarid site and the Mediterranean site. Collembolan abundance responded positively while the Shannon index responded negatively to experimental precipitation at the Mediterranean site only. However, total abundance and collembolan abundance were found to decrease across a mean annual precipitation (MAP) gradient from the arid site to the mesic Mediterranean site. Quantile regression for linear mixed-effects models demonstrated a negative effect of MAP on Acari abundance at the medium level of Acari abundance but weak positive effects of MAP on taxonomic richness and the Shannon index. In conclusion, we found that the distribution of abundance was a poor proxy for predicting the response of the studied litter arthropod assembly to spatial variation in precipitation.

The analysis of spatial variability of precipitation in Poland in the multiyears 1981–2010

The analysis of spatial variability of precipitation in Poland in the multiyears 1981–2010

Improving the precipitation forecasts of the North-American multi model ensemble (NMME) over Sistan basin

Poor forecasting of climate variables at river basin scale, leads to situations which entail considerable risks and losses in various sectors such as the agriculture, the environment and water resources. Lack of accurate sub-seasonal and seasonal precipitation predictions are major management and operation predicaments in the transboundary Sistan Basin, located in Afghanistan and Iran, and selected as the case study in this paper. The outputs of theNorth-American Multi Model Ensemble (NMME), as a seasonalforecasting system, were utilized in the target region. In order to evaluate the performance of the raw outputs of four NMME models (namely: NCEP-CFSv2, CMC-CanCM3, CMC2-CanCM4, NCAR-CCSM4), the individual model ensemble mean was compared to the observations. Results highlighted the need for post-processing of the NMME outputs. For this purpose, three different commonly used methods, including GrandNMME, bias correction quantile mapping (QM) and Copula approaches, alongside a novel hybrid technique, were applied to improve future predictions of precipitation patterns for the hindcast period of 1982–2010 and forecast period of 2012–2016. All four methods were performed for each month in each 0.5-degree cell over the following one to six months. The findings demonstrated the performance of different NMME models were not the same over time and space. Among the models, the NCEP-CFSv2 and CMC2-CanCM4 seemed to best capture the spatial variability of precipitation in the study area. In addition, they performed better in estimating the amounts of precipitation. Among the methods, the QM, the Copula and the hybrid were all successful in improving the geographic patterns of the data. Furthermore, they were all able to enhance the accuracy of the data. At different timescales, the hybrid method showed substantial improvements over the seasonal predictions. Overall, the findings illustrated that collective use of methods may narrow the potential uncertainty in projections of regional changes.

The role of spatial and temporal model resolution in a flood event storyline approach in western Norway

We apply a physical climate storyline approach to an autumn flood event in the West Coast of Norway caused by an atmospheric river to demonstrate the value and challenges of higher spatial and temporal resolution in simulating flood impacts. We use a modelling chain whose outputs are familiar and used operationally, for example to issue flood warnings. With two different versions of a hydrological model, we show that (1) the higher spatial resolution between the global and regional climate model is necessary to realistically simulate the high spatial variability of precipitation in this mountainous region and (2) only with hourly data are we able to capture the fast flood-generating processes leading to the peak streamflow. The higher resolution regional atmospheric model captures the fact that with the passage of an atmospheric river, some valleys receive high amounts of precipitation and others not, while the coarser resolution global model shows uniform precipitation in the whole region. Translating the event into the future leads to similar results: while in some catchments, a future flood might be much larger than a present one, in others no event occurs as the atmospheric river simply does not hit that catchment. The use of an operational flood warning system for future events is expected to facilitate stakeholder engagement.

USO DA GEOTECNOLOGIA PARA A ANÁLISE DA PRECIPITAÇÃO EM CUBATÃO (SP) – CORRELAÇÃO COM A OCORRÊNCIA DE MOVIMENTOS DE MASSA

A distribuição espacial e temporal das chuvas é de fundamental importância para gerenciamento dos recursos naturais. A presença de água relaciona-se com a grande maioria dos casos de instabilização de encostas (vertentes), tendo grande influência na deflagração de processos de movimentos de massa. A pesquisa tem como principal objetivo analisar, em ambiente SIG, a variação temporal e espacial da precipitação na região de Cubatão, por meio da interpolação de dados históricos de precipitação intensa na região. Os dados de pluviometria foram coletados por meio do Banco de Dados Hidrológicos do Departamento de Águas e Energia Elétrica (DAEE) do Estado de São Paulo, de forma gratuita. Foram feitos gráficos de média total mensal de precipitação, assim como mapas de distribuição espacial da média da chuva anual. Tais resultados foram comparados com o evento de 1976 ocorrido e registrado em bibliografias. Como resultado, pôde-se observar que o ano de 1975 foi o ano com maiores valores de médias mensais, chegando a quase 650 mm em janeiro, o que indica que no ano que antecedeu o evento de movimento de massa houve uma chuva acima da média na região, podendo ser um fator considerado deflagrador ou potencializador da ocorrência desses processos geológicos.

Statistical evaluation of gridded precipitation datasets using rain gauge observations over Iran

The present study assessed the accuracy of twenty-three available globally and regionally gridded precipitation products over Iran. The datasets were classified into five different categories based on the data sources used: gauge-only, gauge-satellite, gauge-reanalysis, reanalysis-only, and gauge-satellite-reanalysis. By considering monthly rain gauge observation data as reference, the above precipitation products were assessed based on a variety of metrics over the period 1979 to 2013. The results indicated that the time-series of the spatial averaged precipitation of all the products do reasonably well in tracking the month-to-month variations with the majority of the products underestimating precipitation amounts with respect to the reference rain gauge observations. Overall, the best performances were demonstrated by Asfazari and APHRODITE followed by CHIRPS and GPCC. WFDEI-CRU was the worst performer among the twenty-three gridded products in revealing precipitation tempo-spatial patterns. The results demonstrate the high performance for all products in the west of the country (the Zagros Range) and in all seasons except the summer. The results also indicate that there is a better agreement between rain gauge observations and the gridded products during the rainy seasons (winter, spring and autumn) compared to the dry season (summer). This study improved our knowledge of the suitability of different precipitation gridded product estimates to capture the temporal and spatial variability of precipitation. Furthermore, it is applicable for developing precipitation products and provides valuable guidance for selecting alternative precipitation products to in situ observations.

Latitudinal gradients and ecological drivers of β‐diversity vary across spatial scales in a temperate forest region

AbstractAimOur understanding of the mechanisms driving β‐diversity is still rather rudimentary. This study evaluates the influences of environmental filtering versus spatial scale of regional communities on β‐diversity across latitudes.LocationNorth‐eastern China.MethodsThe β‐diversity was calculated in each regional community. The spatial extent of these “regional communities”, which included five or 10 plots, was ≤ 140 km. A random assembly null model was used to assess the effects of species abundance distribution on the β‐diversity. Moreover, the deviation of observed β‐diversity from a null model (called β‐deviation) was also assessed. The variations of the β values were partitioned into environmental, latitudinal and their joint effects.ResultsThe observed β‐diversity declined with increasing latitude, although the β‐deviations showed a non‐monotonic pattern as the latitude increased at two studied scales. All the regional communities consisting of five or 10 local plots exhibited significantly positive β‐deviations. The total amount of variation in β‐deviations explained by environmental and latitudinal variables increased dramatically with increasing scale. A significant pure environmental effect was observed at both scales, explaining 30% of the variation in β‐deviation for regional communities consisting of five local plots and 58.7% for regional communities consisting of 10 local plots. The spatial variation in precipitation primarily accounted for the β‐gradient.Main conclusionsThis is one of the few multiscale analyses to investigate latitudinal patterns and driving mechanisms of tree β‐diversity in temperate forests. The β‐deviation showed a similar trend of change with latitude, but the variation of β‐deviation explained by the environments and latitude was highly dependent on the scale of regional communities studied. Environmental filtering and the spatial scale of regional communities jointly accounted for the β‐gradient, with environmental filtering appearing to determine the high variation of species turnover along the latitudinal gradient.

Evaluation and Error Correction of the ECMWF Subseasonal Precipitation Forecast over Eastern China during Summer

Subseasonal-to-seasonal (S2S) prediction is a highly regarded skill around the world. To improve the S2S forecast skill, an S2S prediction project and an extensive database have been established. In this study, the European Center for Medium-Range Weather Forecasts (ECMWF) model hindcast, which participates in the S2S prediction project, is systematically assessed by focusing on the hindcast quality for the summer accumulated ten-day precipitation at lead times of 0–30 days during 1995–2014 in eastern China. Additionally, the hindcast error is corrected by utilizing the preceding sea surface temperature (SST). The metrics employed to measure the ECMWF hindcast performance indicate that the ECMWF model performance drops as the lead time increases and exhibits strong interannual differences among the five subregions of eastern China. In addition, the precipitation forecast skill of the ECMWF hindcast is best at approximately 15 days in some areas of Southeast China; after correcting the forecast error, the forecast skill is increased to 30 days. At lead times of 0–30 days, regardless of whether the forecast error is corrected, the root mean square errors are lowest in Northeast China. After correcting the forecast error, the performance of the ECMWF hindcast shows better improvement in depicting the quantity and temporal and spatial variation of precipitation at lead times of 0–30 days in eastern China. The false alarm ratio (FAR), probability of detection (POD), and equitable threat score (ETS) reveal that the ECMWF model has a preferable performance at forecasting accumulated ten-day precipitation rates of approximately 20∼50 mm and indicates an improved hindcast quality after the forecast error correction. In short, adopting the preceding SST to correct the summer subseasonal precipitation of the ECMWF hindcast is preferable.

A Dynamic Approach to Quantitative Precipitation Estimation Using Multiradar Multigauge Network

Effective utilization of the changing precipitation microphysics in real-time radar quantitative precipitation estimation (QPE) is challenging, which requires dynamic adjustment of the radar reflectivity (Z) and rain rate (R) relations. This article develops and demonstrates two dynamic radar rainfall approaches using 16 Doppler weather radars and 4579 surface rain gauges deployed over the Eastern Jiang Huai River Basin (EJRB) in China. Both approaches are derived based on the radar-gauge feedback mechanism. Although the Z-R relations in both approaches are dynamically adjusted within a precipitation system, one is using a single global optimum (SGO) Z-R relation, while the other is using different Z-R relations for different storm cells identified by a storm cell identification and tracking (SCIT) algorithm. Four precipitation events featured by different rainfall characteristics are investigated to evaluate the performances of various QPE methodologies. In addition, the shortterm vertical profile of reflectivity (VPR) clusters is extensively analyzed to resolve the storm-scale characteristics of different storm cells. The evaluation results based on independent gauge observations show that both rainfall approaches with dynamic Z-R relations perform much better than the fixed Z-R relations. The adaptive approach incorporating the SCIT algorithm and real-time gauge measurements has the best performance since it can better capture the spatial variability and evolution of precipitation.

Evaluating the Applicability of the PUSH Framework to Quasi-Global Infrared Precipitation Retrievals at 0.5°/Daily Spatial/Temporal Resolution

Error estimates associated with satellite precipitation retrievals are crucial to allow inferences about the reliability of such products in their operational applications. However, evaluating satellite precipitation error characteristics is challenging because of the inherent temporal and spatial variability of precipitation, measurement errors, and sampling uncertainties, especially at fine temporal and spatial resolutions. The aim of this study is to estimate errors associated with satellite-based infra-red (IR) precipitation retrievals quasi-globally (60°N − 60°S) over land. The error model adopted for this study is the Probability Uncertainty in Satellite Hydrology (PUSH) framework, which is calibrated and validated against the satellite-based Level-3 Dual frequency precipitation radar product at daily resolution (3DPRD) for different Koppen climate zones. PUSH is shown to efficiently estimate errors in the IR retrievals, although its performance depends on the regional climatology. Specifically, the continental climate zone shows better agreement between observed and estimated errors as compared to other regions, which can be attributed to the general spatial homogeneity of precipitation across this zone and better correlation between IR and 3DPRD estimates.

Satellite footprint data from OCO-2 and TROPOMI reveal significant spatio-temporal and inter-vegetation type variabilities of solar-induced fluorescence yield in the U.S. Midwest

Solar-induced chlorophyll fluorescence (SIF) measured from space has been increasingly used to quantify plant photosynthesis at regional and global scales. Apparent canopy SIF yield (SIFyield apparent), determined by fluorescence yield (ΦF) and escaping ratio (fesc), together with absorbed photosynthetically active radiation (APAR), is crucial in driving spatio-temporal variability of SIF. While strong linkages between SIFyield apparent and plant physiological responses and canopy structure have been suggested, spatio-temporal variability of SIFyield apparent at regional scale remains largely unclear, which limits our understanding of the spatio-temporal variability of SIF and its relationship with photosynthesis. In this study, we utilized recent SIF data with high spatial resolution from two satellite instruments, OCO-2 and TROPOMI, together with multiple other datasets. We estimated SIFyield apparent across space, time, and different vegetation types in the U.S. Midwest during crop growing season (May to September) from 2015 to 2018. We found that SIFyield apparent of croplands was larger than non-croplands during peak season (July–August). However, SIFyield apparent between corn (C4 crop) and soybean (C3 crop) did not show a significant difference. SIFyield apparent of corn, soybean, forest, and grass/pasture show clear seasonal and spatial patterns. The spatial variability of precipitation during the growing season could explain the overall spatial pattern of SIFyield apparent. Further analysis by decomposing SIFyield apparent into ΦF and fesc using near-infrared reflectance of vegetation (NIRV) suggests that fesc may be the major driver of the observed variability of SIFyield apparent.

Past and present spatial precipitation variability in the upper middle catchment of the Olifants River basin

Within the context of catchment hydrology, using the Soil and Water Assessment Tool (SWAT) model, this paper attempts to assess the past and present spatial precipitation variability in the upper middle catchment (UMC) of the Olifants River basin. The study shows a strong decreasing trend of east-to-west direction of spatial precipitation with most rainfall concentrated in the eastern part of the area. Within the western part of the UMC, we also noted another decreasing trend of precipitation from south to north with northern areas of the study area receiving the least amount of rainfall. This localized spatial precipitation variability in the area, from past and present, underlines the importance of studies targeting localized areas within a larger and wider river basin like the Olifants where such variations could otherwise been overlooked.

Characterizing precipitation in high altitudes of the western Tibetan plateau with a focus on major glacier areas

AbstractSolid water resources such as glaciers and snow cover are widely distributed in the western Tibetan plateau (WTP), and precipitation is the key supply of them. However, the characteristics of precipitation over the WTP remain unclear due to sparse observations. Using observation‐based gridded data (APHRODITE, GPCC), satellite products (TRMM, GPM), reanalysis data (ERA5, ERA‐Interim, JRA‐55) and weather research and forecasting model (WRF)‐simulation data (HAR10, HAR30), this study investigated the precipitation characteristics in high mountain areas (altitude >2,500 m a.s.l.) of the WTP (26–44°N, 70–85°E) from 2001 to 2013. Results show that annual GPM precipitation (336 mm) is much lower than that of other data sets (570–800 mm) for the WTP and appears to be an outlier; meanwhile, the other data sets show increasing precipitation as grid resolution decreases (becomes coarser). In contrast, high spatial resolution WRF simulations (HAR10, HAR30) yielded considerably higher precipitation in four strongly glacierized alpine areas (Western Himalaya, Karakorum, Tajikistan, and west Kunlun) than the other data sets. When compared to precipitation estimated using the water balance in nine glacierized catchments of the Upper Indus River Basin, the HAR data sets more reasonably represent the amount of precipitation in high mountain areas than the other data sets. The surface albedo, snow cover extent, and snow cover duration observed by satellites further indicate that the HAR data sets yield reasonable spatial variability of precipitation. This implies that the commonly used data sets (such as observation data and satellite products) underestimate the precipitation in high mountain areas. According to the HAR10 data, the four major glacierized areas on the WTP have similar precipitation amounts in summer and autumn, and the winter–spring contribution to annual precipitation is at least 70% in three of these areas (Western Himalaya, Karakorum, and Tajikistan). This pattern indicates that precipitation over the high‐altitude areas in WTP is mainly controlled by the mid‐latitude westerlies. The annual precipitation in these areas is over 1,000 mm, which is comparable to that of the southeast TP but much larger than that on the central plateau. Therefore, the spatial precipitation pattern across the TP is ‘wet east and west, dry middle’.

Evaluation and Projection of Regional Climate over East Asia in CORDEX-East Asia Phase I Experiment

This study investigates the performance of simulated precipitation and estimates future changes in precipitation in CORDEX-East Asia Phase I. In the Historical experiment (1981–2005), a global climate model used as a lateral boundary condition does not realistically simulate the timing and intensity of the East Asian summer monsoon. Hence, it overestimates precipitation over East Asia. Generally, the results of the regional climate models also show similar bias characteristics to that of the large-scale forcing data. The individual biases of the regional climate model vary according to a model configuration, such as physical parameterization schemes. However, when bias correction is applied to data, the spatial variability and spatial correlation of the long-term mean precipitation become similar to the observations, and the annual cycle of precipitation is much improved. The two future experiments in the mid-twenty-first century period (2025–2049), show that mean and extreme precipitation amounts increase over the Korean Peninsula and northern China compared to the frequency of wet days. The increment of the low-level water vapor in all seasons can be attributed to the increased precipitation amounts; moreover, the East Asian summer monsoon is enhanced in mid-latitudes and lasts longer in summer owing to the strengthened western North Pacific Subtropical High. The increasing southerly wind from the East Asian summer monsoon over eastern China and the Korean Peninsula results in favorable conditions for the increase in precipitation.

Characteristics of Ice Cloud–Precipitation of Warm Season Mesoscale Convective Systems over the Great Plains

AbstractIn this study, the mesoscale convective systems (MCSs) are tracked using high-resolution radar and satellite observations over the U.S. Great Plains during April–August from 2010 to 2012. The spatiotemporal variability of MCS precipitation is then characterized using the Stage IV product. We found that the spatial variability and nocturnal peaks of MCS precipitation are primarily driven by the MCS occurrence rather than the precipitation intensity. The tracked MCSs are further classified into convective core (CC), stratiform rain (SR), and anvil clouds regions. The spatial variability and diurnal cycle of precipitation in the SR regions of MCSs are not as significant as those of MCS precipitation. In the SR regions, the high-resolution, long-term ice cloud microphysical properties [ice water content (IWC) and ice water paths (IWPs)] are provided. The IWCs generally decrease with height. Spatially, the IWC, IWP, and precipitation are all higher over the southern Great Plains than over the northern Great Plains. Seasonally, those ice and precipitation properties are all higher in summer than in spring. Comparing the peak timings of MCS precipitation and IWPs from the diurnal cycles and their composite evolutions, it is found that when using the peak timing of IWPSR as a reference, the heaviest precipitation in the MCS convective core occurs earlier, while the strongest SR precipitation occurs later. The shift of peak timings could be explained by the stratiform precipitation formation process. The IWP and precipitation relationships are different at MCS genesis, mature, and decay stages. The relationships and the transition processes from ice particles to precipitation also depend on the low-level humidity.

Trend of extreme precipitation indices and analysis of long-term climate variability in the Upper Awash basin, Ethiopia

Assessing the spatial and temporal variability of climate data is one of the basic requirements to solve the hydrological and water management problems. In this manuscript, a comprehensive assessment of data quality, precipitation concentration index (PCI), Mann-Kendall (MK) trend test, and extreme climate change indices analyses were performed. The standard normal homogeneity test (SNHT), the Pettitt test, the Buishand range test, and the Von Neumann ratio test were used for homogeneity analysis, and most of the climate stations exhibited homogenous precipitation series. The annual mean and dry season PCI values demonstrated higher spatial and temporal variability or irregular distribution of precipitation, whereas PCI in the wetter seasons indicated low precipitation concentration in the Upper Awash basin. The MK trend test exhibited a significantly increasing trend of maximum temperature; however, the trend of mean annual and extreme precipitation events was insignificant for the majority of stations. Moreover, the magnitude and trend of ten main extreme precipitation indices were constructed. Unlike the mean annual precipitation, larger values of the extreme 1-day (Rx1day) and 5-day (Rx5day) annual precipitation were obtained in the downstream areas of the basin which could signify the prevalence higher flood risk in this portion of the basin. The highest predicted 100-year annual maximum daily (AMD) precipitation was obtained at Zikuala station as 128.5 mm. Statistical analysis of the magnitude and trend of extreme precipitation indices and spatial variability of climate data is imperative for the integrated water resource planning and management decisions.

Temporal variability of the highest and the lowest monthly precipitation totals in the Polish Carpathian Mountains (1881–2018)

Extreme climatic phenomena include prolonged heavy precipitation as well as long-lasting absence thereof. They are a consequence of weather anomalies and have many dangerous effects such as floods and droughts. This study aims to characterise the annual and long-term variability of the highest (Pmax) and lowest (Pmin) monthly precipitation totals and their relationship with atmospheric circulation. To achieve the above, use is made of 14 secular series (1881–2018) of precipitation from the Polish Carpathians and the calendar of circulation types over southern Poland prepared by T. Niedźwiedź (1981, 2019). On account of the variation in their relief, the Polish Carpathians are an area with a very great temporal and spatial variability in precipitation, ranging from complete absence to 500 mm per month. Pmax demonstrates a more noticeable annual frequency pattern, with a predominance in summer months, while Pmin shows smaller variations in individual months. Both Pmax and Pmin are characterised by irregular fluctuations in precipitation totals, with no statistically significant trend in their changes, which reflects the absence of a trend as regards overall precipitation volumes in this area. The study confirms an influence of the direction of air mass advection and (anti)cyclonicity of flow on Pmax and Pmin.

A Novel Method of Quantifying Catchment‐Wide Average Peak Propagation Speed in Hillslopes: Fast Hillslope Responses are Detected During Annual Floods in a Steep Humid Catchment

AbstractThe lag time between rainfall input and discharge output—that is, the response speed of a catchment—is a key parameter for flood prediction but is difficult to quantify. Here we propose a new method to quantify catchment‐wide average peak propagation speed in hillslopes based on measurements conducted in a steep 4.5‐km2 catchment. The peak lag time of the catchment was partitioned into lag times in the hillslope and channel. Peak propagation speed was calculated from flow path length divided by lag time. We verified the results and evaluated the applicability and uncertainty of this method. This method can be applied during intense storms with identifiable peak relationships between rainfall and discharge. The effect of spatial variation in precipitation was insignificant in the study catchment. The increase in rainfall intensity and the rainfall accumulated prior to peak rainfall increased peak propagation speed. The method used to characterize flow path length from distributed values introduced some uncertainty. We calculated modal lengths using linear and logarithmic scales and various bin widths. These calculations resulted in small differences in modal channel length but led to more than tenfold differences in modal hillslope length. Thus, uncertainties for peak propagation speed across all hillslopes varied by one order of magnitude. Hillslope lag times were less than 2 min and peak propagation speed in the hillslopes ranged from 0.04 to 4.3 m/s for floods with recurrence intervals of one to several years. The proposed method and calculated data should improve prediction accuracy for extreme floods.

Analysis of the Silting Rate in the “Hachef” Dam Situated in Northern Morocco in the Context of Global Change

The Moroccan annual dam silting corresponds to a loss in storage capacity of the reservoirs of about 75 million m3 per year. Land use metamorphosis and the ongoing climate changes are likely to accelerate the process of soil degradation and erosion. In this delicate context, Morocco will have to provide appropriate responses in terms of adaptation and remediation strategies to the degradation of soil and water resources. The objectives of this paper are to characterize the Specific Degradation (SD) of the Tangier basin through the study of the silting of the watershed located upstream the Hachef dam and to analyze the silting rate of the Hachef dam according to the variability of precipitations and the dynamics of the vegetation convent. The adopted approach is based on the analysis of the bathymetric surveys of the Hachef Dam to characterize the SD and the analysis of the silting rate based on the characterization of the spatial and temporal variability of the two key factors of water erosion. The results of processing the bathymetric surveys over a 19-year analysis period (1995-2014) show an annual average total silting of about 11.46 Mm3 and a corresponding SD of about 36.7 t⋅ha−1⋅yr−1. This study shows the significant influence of the spatial and temporal variability of precipitation and vegetation cover on the silting dynamics of dams.

Application of RS/GIS in Conservation Studies for Surface and Groundwater Harvesting in Cold Arid Regions of Northwestern Himalayas

Abstract.The availability of erratic rainfall and high evapotranspiration causes temporal and spatial variability of water thereby causing crop yield reduction and crop failure. The potential of water harvesting (WH) both groundwater as well as surface water to mitigate the spatial and temporal variability of precipitation. One technique for water harvesting (WH) is to collect excess runoff water both rain and snowmelt, store it for agricultural purposes during dry spells. The present work accentuated the expediency of remote sensing (RS) and geographic information system (GIS) applications in water harvesting studies. The resultant water harvesting potential map prepared was thus classified into three WH potential zones namely, high, medium and low covering an area of 32.82, 10320.10, and 7596.18 ha (<1%, 57.49%, and 42.32%) respectively. The groundwater map in the area was also classified as high potential areas covering 1421.69 ha (7.92%), medium potential areas covering 8762.69 ha (48.81%), and low potential areas covering 7764.72 ha (43.25%). The integrated remote sensing (RS), Geographical Information System (GIS), Soil and Water Assessment Tool (SWAT), and analytical hierarchy process (AHP) were found to be efficient methods to recover water and to select suitable water and groundwater harvesting sites in order to ensure better water accessibility to the people for domestic, irrigation and other activities in cold arid regions of northwestern Himalayas. Keywords: Analytical hierarchy process, Geographic Information System, Groundwater harvesting, Remote sensing, Spatial variability, Temporal variability, Water harvesting.